From b6c197baa31f0f01a64c1f82d0cffddf1b568f3c Mon Sep 17 00:00:00 2001
From: JamesPino <JamesPino@users.noreply.github.com>
Date: Tue, 16 Apr 2024 18:52:32 +0000
Subject: [PATCH] chore: update memote history report

---
 snapshot_report.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/snapshot_report.html b/snapshot_report.html
index 8139163..fff05c4 100644
--- a/snapshot_report.html
+++ b/snapshot_report.html
@@ -20,7 +20,7 @@
 <body style="background-color: rgba(177, 212, 237, 0.1)">
   <app-root></app-root>
   <script>
-    window.data = {"meta":{"timestamp":"2024-04-09 21:02:50.955808","platform":"Linux","release":"6.5.0-1017-azure","python":"3.10.6","packages":{"click":"8.1.7","click-configfile":"0.2.3","click-log":"0.4.0","six":"1.16.0","future":"1.0.0","pytest":"7.4.4","gitpython":"3.1.43","pygithub":"1.59.1","pandas":"2.2.1","jinja2":"3.1.3","cookiecutter":"2.6.0","cobra":"0.29.0","ruamel.yaml":"0.18.6","sympy":"1.12","sqlalchemy":"2.0.29","requests":"2.31.0","numpydoc":"1.7.0","pylru":"1.2.1","pandera":"0.18.3","jsonschema":"4.21.1","depinfo":"2.2.0","importlib-resources":"6.4.0","black":"not installed","isort":"not installed","tox":"not installed"}},"tests":{"test_excreted":{"duration":3.9052479989999824,"result":"failed","title":"Models ability to excrete metabolites","summary":"This test addresses the models ability to excrete metabolites.\nModels are optimized to produce the given exchange reaction and\nsimulated with natural medium.","message":"Model is able to excrete 1 and unable to          excrete 16","data":{"TP":["sucr"],"FN":["3pg","acac","acmana","arab__D","arbt","bhb","g15lac","gam1p","glc__D","lcts","malt","phyt","pnto__R","pro__L","pyr","rib__D"]},"format_type":"number","metric":16},"test_metabolite_annotation_presence":{"duration":0.0007474469999806388,"result":"failed","title":"Presence of Metabolite Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field for each metabolite, irrespective of the type of\nannotation i.e. specific database  cross-references, ontology terms,\nadditional information. For this test to pass the model is expected to\nhave metabolites and each of them should have some form of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Metabolite object of the\nmodel is unset or empty.","message":"A total of 31 metabolites (3.35%) lack any form of annotation:\n38ch2gtp_c, gcaro_c, lyc_c, mocogdp_c, acmama_c, ...","data":["38ch2gtp_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.03354978354978355},"test_reaction_annotation_presence":{"duration":0.0009760130000131539,"result":"failed","title":"Presence of Reaction Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field for each reaction, irrespective of the type of\nannotation i.e. specific database  cross-references, ontology terms,\nadditional information. For this test to pass the model is expected to\nhave reactions and each of them should have some form of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Reaction object of the\nmodel is unset or empty.","message":"A total of 38 reactions (3.74%) lack any form of annotation:\nGTPC, LYCBC1, MOGDS, AMAA, CSND, ...","data":["GTPC","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","GLCP4","GLCP3"],"format_type":"count","metric":0.0374384236453202},"test_gene_product_annotation_presence":{"duration":0.0005521010000393289,"result":"failed","title":"Presence of Gene Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field (extended by FBC package) for each gene product,\nirrespective of the type of annotation i.e. specific database,\ncross-references, ontology terms, additional information. For this test to\npass the model is expected to have genes and each of them should have some\nform of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Gene object of the\nmodel is unset or empty.","message":"A total of 97 genes (11.00%) lack any form of         annotation:\ncscB, Synpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211,\nSynpcc7942_1656, ...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_metabolite_annotation_overview":{"duration":{"pubchem.compound":0.0009133959999871877,"kegg.compound":0.0006116819999988365,"seed.compound":0.0005398189999823444,"inchikey":0.0005580929999950968,"inchi":0.000522155999988172,"chebi":0.0005036499999846455,"hmdb":0.000543756000013218,"reactome":0.0005063159999849631,"metanetx.chemical":0.0004464439999765091,"bigg.metabolite":0.00045982900002172755,"biocyc":0.0004991520000316996},"result":{"pubchem.compound":"failed","kegg.compound":"failed","seed.compound":"failed","inchikey":"failed","inchi":"failed","chebi":"failed","hmdb":"failed","reactome":"failed","metanetx.chemical":"failed","bigg.metabolite":"failed","biocyc":"failed"},"title":"Metabolite Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each metabolite annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all metabolites consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Metabolite of\nthe model match with a selection of common biochemical databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"pubchem.compound":"The following 924 metabolites (100.00%) lack annotation for\npubchem.compound:         dhf_c, dudp_c, 3omrsACP_c, trnaglu_c,\npre6a_c, ...","kegg.compound":"The following 341 metabolites (36.90%) lack annotation for\nkegg.compound:         ugmd_c, 3a2oxpp_c, amylose_c, hdeACP_c, pcox_u,\n...","seed.compound":"The following 289 metabolites (31.28%) lack annotation for\nseed.compound:         ugmd_c, 3a2oxpp_c, amylose_c, hdeACP_c,\nphycy_c, ...","inchikey":"The following 924 metabolites (100.00%) lack annotation for inchikey:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","inchi":"The following 924 metabolites (100.00%) lack annotation for inchi:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","chebi":"The following 235 metabolites (25.43%) lack annotation for chebi:\n3a2oxpp_c, amylose_c, hdeACP_c, pcox_u, octe9ACP_c, ...","hmdb":"The following 509 metabolites (55.09%) lack annotation for hmdb:\n3omrsACP_c, trnaglu_c, pre6a_c, 3hhexACP_c, glyald_c, ...","reactome":"The following 924 metabolites (100.00%) lack annotation for reactome:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","metanetx.chemical":"The following 247 metabolites (26.73%) lack annotation for\nmetanetx.chemical:         3a2oxpp_c, amylose_c, phycy_c, bm_pigm_c,\nu3hga2_c, ...","bigg.metabolite":"The following 156 metabolites (16.88%) lack annotation for\nbigg.metabolite:         tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","biocyc":"The following 356 metabolites (38.53%) lack annotation for biocyc:\n3hhexACP_c, db4p_c, ugmd_c, 3a2oxpp_c, tdec2eACP_c, 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Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each reaction annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all reactions consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Reaction of\nthe model match with a selection of common biochemical databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"rhea":"The following 605 reactions (59.61%) lack annotation for rhea:\nEX_gln__L_e, O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1, ...","kegg.reaction":"The following 624 reactions (61.48%) lack annotation for\nkegg.reaction:         EX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e,\nO2tcx, ...","seed.reaction":"The following 520 reactions (51.23%) lack annotation for\nseed.reaction:         O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1,\nHISTDa, ...","metanetx.reaction":"The following 411 reactions (40.49%) lack annotation for\nmetanetx.reaction:         O2tcx, AOXPBDC, BIOMASS_PIGMENTS,\nBIOMASS__1, HISTDa, ...","bigg.reaction":"The following 166 reactions (16.35%) lack annotation for\nbigg.reaction:         EX_tre_e, EX_man_e, EX_galt_e, EX_arab__L_e,\nEX_acgam_e, ...","reactome":"The following 1015 reactions (100.00%) lack annotation for reactome:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, ADPT, ...","ec-code":"The following 544 reactions (53.60%) lack annotation for ec-code:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, O2tcx, ...","brenda":"The following 1015 reactions (100.00%) lack annotation for brenda:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, ADPT, ...","biocyc":"The following 606 reactions (59.70%) lack annotation for biocyc:\nEX_hco3_e, O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1, ..."},"data":{"rhea":["EX_gln__L_e","O2tcx","AOXPBDC","BIOMASS_PIGMENTS","BIOMASS__1","ACOATA","3HAD160","RNDR3","HISTDa","DMBZIDS2","ZCAROTDH2","CMPA_1","U23GAAT2","HOXGfx","LPOR","GCALDDy","MSBENZMT","DESAT18a","PHYFXOR","TMPPP_1","RNDR1","HEMEAS_1","DHORD3um","HBZNPT","COCHL_1","HISTDb","H4THDPR","GLCS3","PRAGSr","UDCPDPS","G1PACT","3HAD60","PGI","KAS14","PQH2tum","O2tu","O2tpp","3HAD80","3OAR160","PPK","PHYTES2_1","GLUSfx","GLUTRR","PSIum","FOLD3","MEHLER_1","3OAS140","PPK2","IPDPS_syn","GLYDHDA","H4THDPS","EAR60y","ADOCBLS","PDS2_1","O2tex","GF6PTA","PGMT","GLCP2_1","AGDI_1","LPADSS2","EX_ptrc_e","EAR120y","HEX7","CYTBD4cm","PRE3BS","PPPGO2_1","BIOMASS_DNA","DNAMTn2r","BIOMASS_CELL_WALL","RB15BPtcx","3HAD180","3OAS80","AMPMS3","G1PCTYT","UHGADA2","DHNANT","HGYDAS","3PGtcx","PAPSR","BIOMASS_COFACTORS","DM_h2_c","DPOR","3HAD140","ARGOXRum","BCAROHX2","HPPK","GTPCII","GLCBRAN3","DB4PS","RBFSa","GLUTRS","EAR160y","PDX5PS2","KARI_23dhmp_1","ASPOb","RBFSb_1","SUCDum","DVOCHR_1","H2CO3_NAt_syn","MPOMT_1","PC17M_1","NDHPQRum","CYNL","CYOOum","BPNT2","FNOR_1","DMTPHT","PC6YM_1","CYRDAAT","MECDPDHf","Htcx","3HAD40_2","ZCAROTDH1","CYRDAR","BIOMASS_MEM_LIPIDS","HCO3tcx","GLYALDDy","BIOMASS_PROTEIN","3OAR40_2","RNDR2","NPDPS","3OAS100","MAN6PI","HPROb","3OAS120","EAR180y","3OAS60","EAR40y","TKT1","PKETF","NDHPQRcm","TRDR","NTRIRfx","DHNCOAS","MCOATA","PKETX","PMPK","HTHRPDH","UAGAAT2","PRPPS","CITMS","BCT1_syn","TRDRf","ADCYRS","PC6AR_1","TRSARyr","CYNTtabcpp","RBPCcx","DHNPA_1","BIOMASS_RNA","DM_dialurate_c","CO2tex","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","PQH2tcm","2PGLYCtcx","PDS1_1","3OAS180","EAR80y","DM_5drib_c","SK_amylose_c","EAR140y","CYTBD4um","DHPPDA","BCAROHX","SK_14glucan_c","SK_glycogen_c","EX_o2_e","EX_co2_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","UAAGDS","ARGDHpp","DMPPS_syn","ANS2","3OAS160","ACHBSb","MPOMOR_1","EX_cynt_e","AHSERL2_1","PEPC","NTRARf2","G6PDA","Nat_Kpp","CA2t2pp","SULR_2","UGMDDS","GLCDBRAN3","RPI","FMNRy_1","PGPP_OLE_PALM","H2Otcx","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","DM_amob_c","OPMEACPD","OPMEACPR","EX_photon530_e","EX_photon550_e","AGPAT160","EX_photon570_e","EX_photon590_e","EX_photon610_e","AGPATACP_HDE_PALM","LEUtex","BTS6","QUERT","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","GLNtex","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","CYNTtex","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","GLUDGS_HDE_HDE","TYRTRS","DAGK160","DAGK_HDE_PALM","DAGK161","SQDGS_PALM_PALM","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","PTRCtex","DGDGS_HDE_HDE","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","PROTRS","GLYTRS","CYSTRS","ARGTRS","TRPTRS","HISTRS","CO2tpp","PHETRS","ASNTRS","ASPTRS","THRTRS","LEUTRS","ILETRS","CHLADMT_1","LYSTRS","AOXSr2","LIPOS2","ALATRS","TRNFE","VALTRS","FMETTRS","BACCL","BTNPL2","LIPAMPL_1","LIPOCT","LIPATPT_1","ZXANHX","PHOA410um","PHOA430um","OGMEACPR","PHOA450um","PHOA470um","PHOA490um","PHOA510um","PHOA530um","PLYCOI","PHOA550um","SAMTRI","EPXQR","PHOA570um","PHOA590um","PHOA610um","ZCARDS","PHOA630um","PHOA650um","PHOA670um","PHOA690um","DM_pho_loss_c","ETCHLAS","ETBCARO","COLIPAabcex","MLDCP1App","CDPGLC46DH","AACPS6","ALDR18","ALDDC17","THZT","MLDCP1Bpp","PHYPQOX","MLDCP2App","MLDCP2Bpp","AGM4Pt2pp","AGMt2pp","CXANHX","OGMEACPS","EGMEACPR","DXYTST","OANTS","ACGAMT","Htabcpp","ETAPCPSII","STCHLPSIum","DEXZEAX","PFOR","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","GLYCOX1","UM4PL","UM3PL","PAPPT3","OANTIabcpp","OANTILpp","MDDCP1pp","MDDCP2pp","STACPSI","MLTGY1pp","ETCPC","GLYCOX2","NO2tabcpp","MLTGY2pp","MLTGY3pp","MLTGY4pp","AGM4PA","AM3PA","AM4PA","SK_fum_c","DM_succ_c","AGM3PApp","AGM4PApp","UM4PCP","SK_akg_c","NGAM_D1um","PSICRum","AM4PCP","4PCP","AGM4PCP","AGMH","PSIICRum","DM_ac_c","AGM3PH","DM_lac__D_c","NGAM","AGM4PH","LADGMDH","CELLSYN","ALAALAabcpp","4PEPTabcpp","ADPGLC","DALAabcpp","ZISO","3OAR180","3OAR140","PAPA160","PHEOASE","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","MCTP2App","MCTP1App","MCTP1Bpp","ACLSa","PAPA_OLE_PALM","ACLSb","PHEOX_1","OPMEACPS","EAR100y","EHGLAT","KAS15","PHYTK","NDH_1_4_um_copy2","KARI_1","3HAD120","OGMEACPD","CITCIa","DAGK_OLE_HDE","DAGK_OLE_PALM","3HAD100","3OAR120","3OAR60","3OAR100","3OAR80","NDH_1_1_um_copy1","NDH_1_4_um_copy1","PCHLDA430","PCHLDA650","GGCLUT2","ANHMK","RNDR4","PSICSum","CBFCum","SUCR","CLt3_1pp","Ktu","THBTGT","FDH6","PCXHtpp","THISAT","PSIIum","ATPSum","CYSDES","MDDEP1pp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","MDDCP3pp","MDDCP4pp","MDDCP5pp","MDDEP2pp","MDDEP3pp","MDDEP4pp","MNHNAtpp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX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tion":0.40492610837438425,"bigg.reaction":0.16354679802955666,"reactome":1.0,"ec-code":0.5359605911330049,"brenda":1.0,"biocyc":0.5970443349753695},"score":{"rhea":0.40394088669950734,"kegg.reaction":0.38522167487684733,"seed.reaction":0.48768472906403937,"metanetx.reaction":0.5950738916256157,"bigg.reaction":0.8364532019704434,"reactome":0.0,"ec-code":0.46403940886699513,"brenda":0.0,"biocyc":0.40295566502463054}},"test_gene_product_annotation_overview":{"duration":{"refseq":0.0005192000000420194,"uniprot":0.0005281570000192914,"ecogene":0.0004815199999939068,"kegg.genes":0.00046704300001465526,"ncbigi":0.00039671100000759907,"ncbigene":0.00046397700003808495,"ncbiprotein":0.00046917600002416293,"ccds":0.0004575649999765119,"hprd":0.000480737999964731,"asap":0.000457745000005616},"result":{"refseq":"failed","uniprot":"failed","ecogene":"failed","kegg.genes":"failed","ncbigi":"failed","ncbigene":"failed","ncbiprotein":"failed","ccds":"failed","hprd":"failed","asap":"failed"},"title":"Gene Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each gene annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all gene products consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Gene of\nthe model match with a selection of common genome databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"refseq":"The following 882 genes (100.00%) lack annotation for refseq:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","uniprot":"The following 882 genes (100.00%) lack annotation for uniprot:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ecogene":"The following 882 genes (100.00%) lack annotation for ecogene:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","kegg.genes":"The following 882 genes (100.00%) lack annotation for kegg.genes:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbigi":"The following 113 genes (12.81%) lack annotation for ncbigi:\nSYNPCC7942_RS12985, Synpcc7942_2454, SYNPCC7942_RS03125,\nSynpcc7942_0034, Synpcc7942_0413, ...","ncbigene":"The following 882 genes (100.00%) lack annotation for ncbigene:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbiprotein":"The following 882 genes (100.00%) lack annotation for ncbiprotein:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ccds":"The following 882 genes (100.00%) lack annotation for ccds:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","hprd":"The following 882 genes (100.00%) lack annotation for hprd:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","asap":"The following 882 genes (100.00%) lack annotation for asap:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ..."},"data":{"refseq":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS12985","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","Synpcc7942_2454","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS03125","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","Synpcc7942_0034","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","Synpcc7942_0413","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13375","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7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Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in metabolite annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those metabolites whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"pubchem.compound":"There are no metabolite annotations for the pubchem.compound database.","kegg.compound":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nkegg.compound         database:","seed.compound":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nseed.compound         database:","inchikey":"There are no metabolite annotations for the inchikey database.","inchi":"There are no metabolite annotations for the inchi database.","chebi":"A total of 117 metabolite annotations (16.98%) do not match the\nregular expression patterns defined on identifiers.org for the chebi\ndatabase: tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","hmdb":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the hmdb\ndatabase:","reactome":"There are no metabolite annotations for the reactome database.","metanetx.chemical":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nmetanetx.chemical         database:","bigg.metabolite":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nbigg.metabolite         database:","biocyc":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the biocyc\ndatabase:"},"data":{"pubchem.compound":[],"kegg.compound":[],"seed.compound":[],"inchikey":[],"inchi":[],"chebi":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","mpt_c","moco_c","mptamp_c","fdxo_2_2_c"],"hmdb":[],"reactome":[],"metanetx.chemical":[],"bigg.metabolite":[],"biocyc":[]},"format_type":"percent","metric":{"pubchem.compound":1.0,"kegg.compound":0.0,"seed.compound":0.0,"inchikey":1.0,"inchi":1.0,"chebi":0.16981132075471697,"hmdb":0.0,"reactome":1.0,"metanetx.chemical":0.0,"bigg.metabolite":0.0,"biocyc":0.0},"score":{"pubchem.compound":0.0,"kegg.compound":1.0,"seed.compound":1.0,"inchikey":0.0,"inchi":0.0,"chebi":0.8301886792452831,"hmdb":1.0,"reactome":0.0,"metanetx.chemical":1.0,"bigg.metabolite":1.0,"biocyc":1.0}},"test_reaction_annotation_wrong_ids":{"duration":{"rhea":0.0021878270000001976,"kegg.reaction":0.0010702300000389187,"seed.reaction":0.0012189159999707044,"metanetx.reaction":0.001181877999954395,"bigg.reaction":0.0014865969999959816,"reactome":0.0005209130000025652,"ec-code":0.0015411990000302467,"brenda":0.0004772110000317298,"biocyc":0.001119872000003852},"result":{"rhea":"failed","kegg.reaction":"passed","seed.reaction":"passed","metanetx.reaction":"passed","bigg.reaction":"passed","reactome":"failed","ec-code":"failed","brenda":"failed","biocyc":"passed"},"title":"Reaction Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in reaction annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those reaction whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"rhea":"A total of 20 reaction annotations (1.97%) do not match the\nregular expression patterns defined on identifiers.org for the rhea\ndatabase: Cobalt2abcppI, SPMDabcpp, CA2abcpp, ARGabcpp, MNabc_1, ...","kegg.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nkegg.reaction         database:","seed.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nseed.reaction         database:","metanetx.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nmetanetx.reaction         database:","bigg.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nbigg.reaction         database:","reactome":"There are no reaction annotations for the reactome database.","ec-code":"A total of 16 reaction annotations (1.58%) do not match the\nregular expression patterns defined on identifiers.org for the ec-code\ndatabase: HEMEAS_1, UDCPDPS, PFK_3, DNMPPA, PPNCL3, ...","brenda":"There are no reaction annotations for the brenda database.","biocyc":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the biocyc\ndatabase:"},"data":{"rhea":["Cobalt2abcppI","SPMDabcpp","CA2abcpp","ARGabcpp","MNabc_1","MG2uabcpp","PTRCabcpp","NI2uabcpp","Kabcpp","CUabcpp","MOBDabcpp","FE3abcpp","PIuabcpp","LEUabcpp","SULabcpp","NO3abcpp","GLNabcpp","MPTAT","MDH","PC6YM"],"kegg.reaction":[],"seed.reaction":[],"metanetx.reaction":[],"bigg.reaction":[],"reactome":[],"ec-code":["HEMEAS_1","UDCPDPS","PFK_3","DNMPPA","PPNCL3","HPYRRy","PROAKGOX1","CA2abcpp","FBA3","GLUTRS","GART","GTHRDH_syn","PDH","IG3PS","FALDH2","ASPO5"],"brenda":[],"biocyc":[]},"format_type":"percent","metric":{"rhea":0.019704433497536946,"kegg.reaction":0.0,"seed.reaction":0.0,"metanetx.reaction":0.0,"bigg.reaction":0.0,"reactome":1.0,"ec-code":0.015763546798029555,"brenda":1.0,"biocyc":0.0},"score":{"rhea":0.9802955665024631,"kegg.reaction":1.0,"seed.reaction":1.0,"metanetx.reaction":1.0,"bigg.reaction":1.0,"reactome":0.0,"ec-code":0.9842364532019704,"brenda":0.0,"biocyc":1.0}},"test_gene_product_annotation_wrong_ids":{"duration":{"refseq":0.00044072400004324663,"uniprot":0.00040943499999457345,"ecogene":0.0003664050000224961,"kegg.genes":0.0003530799999680312,"ncbigi":0.001048668999999336,"ncbigene":0.000355043000013211,"ncbiprotein":0.00038734299999987343,"ccds":0.00035341000000244094,"hprd":0.0003519279999864011,"asap":0.0003479090000269025},"result":{"refseq":"failed","uniprot":"failed","ecogene":"failed","kegg.genes":"failed","ncbigi":"failed","ncbigene":"failed","ncbiprotein":"failed","ccds":"failed","hprd":"failed","asap":"failed"},"title":"Gene Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in reaction annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those genes whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"refseq":"There are no gene annotations for the refseq database.","uniprot":"There are no gene annotations for the uniprot database.","ecogene":"There are no gene annotations for the ecogene database.","kegg.genes":"There are no gene annotations for the kegg.genes database.","ncbigi":"A total of 769 gene annotations (87.19%) do not match the\nregular expression patterns defined on identifiers.org for the ncbigi\ndatabase: SYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbigene":"There are no gene annotations for the ncbigene database.","ncbiprotein":"There are no gene annotations for the ncbiprotein database.","ccds":"There are no gene annotations for the ccds database.","hprd":"There are no gene annotations for the hprd database.","asap":"There are no gene annotations for the asap database."},"data":{"refseq":[],"uniprot":[],"ecogene":[],"kegg.genes":[],"ncbigi":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7942_RS09290","SYNPCC7942_RS12700","SYNPCC7942_RS00460","S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Metabolite Identifier Namespace","summary":"In well-annotated models it is no problem if the pool of main identifiers\nfor metabolites consists of identifiers from several databases. However,\nin models that lack appropriate annotations, it may hamper the ability of\nother researchers to use it. Running the model through a computational\npipeline may be difficult without first consolidating the namespace.\n\nHence, this test checks if the main metabolite identifiers can be\nattributed to one single namespace based on the regex patterns defined at\nhttps://identifiers.org/\n\nImplementation:\nGenerate a table with each column corresponding to one\ndatabase from the selection and each row to a metabolite identifier. A\nBoolean entry indicates whether the identifier matches the regular\nexpression of the corresponding database. Since the Biocyc pattern matches\nbroadly, we assume that any instance of an identifier matching to Biocyc\nAND any other database pattern is a false positive match for Biocyc and\nthus set it to ``false``. Sum the positive matches for each database and\nassume that the largest set is the 'main' identifier namespace.","message":"1 metabolite identifiers (0.11%) deviate from the largest found\nnamespace (bigg.metabolite): cyst-L_c","data":["cyst-L_c"],"format_type":"count","metric":0.0010822510822510823},"test_reaction_id_namespace_consistency":{"duration":0.008410891000039555,"result":"passed","title":"Uniform Reaction Identifier Namespace","summary":"In well-annotated models it is no problem if the pool of main identifiers\nfor reactions consists of identifiers from several databases. However,\nin models that lack appropriate annotations, it may hamper the ability of\nother researchers to use it. Running the model through a computational\npipeline may be difficult without first consolidating the namespace.\n\nHence, this test checks if the main reaction identifiers can be\nattributed to one single namespace based on the regex patterns defined at\nhttps://identifiers.org/\n\nImplementation:\nGenerate a pandas.DataFrame with each column corresponding to one\ndatabase from the selection and each row to the reaction ID. A boolean\nentry indicates whether the metabolite ID matches the regex pattern\nof the corresponding database. Since the Biocyc pattern matches quite,\nassume that any instance of an identifier matching to Biocyc\nAND any other DB pattern is a false positive match for Biocyc and then set\nthe boolean to ``false``. Sum the positive matches for each database and\nassume that the largest set is the 'main' identifier namespace.","message":"0 reaction identifiers (0.00%) deviate from the largest found\nnamespace (bigg.reaction):","data":[],"format_type":"count","metric":0.0},"test_model_id_presence":{"duration":0.0001726730000086718,"result":"passed","title":"Model Identifier","summary":"The MIRIAM guidelines require a model to be identified via an ID.\nFurther, the ID will be displayed on the memote snapshot\nreport, which helps to distinguish the output clearly.\n\nImplementation:\nCheck if the cobra.Model object has a non-empty \"id\"\nattribute, this value is parsed from the \"id\" attribute of the <model> tag\nin the SBML file e.g. <model fbc:strict=\"true\" id=\"iJO1366\">.","message":"The model ID is syn_elong","data":"syn_elong","format_type":"raw","metric":0.0},"test_genes_presence":{"duration":0.0002644739999482226,"result":"passed","title":"Total Genes","summary":"A metabolic model can still be a useful tool without any\ngenes, however there are certain methods which rely on the presence of\ngenes and, more importantly, the corresponding gene-protein-reaction\nrules. This test requires that there is at least one gene defined.\n\nImplementation:\nCheck if the cobra.Model object has non-empty \"genes\"\nattribute, this list is populated from the list of fbc:listOfGeneProducts\nwhich should contain at least one fbc:geneProduct.","message":"882 genes are defined in the model.","data":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS12985","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","Synpcc7942_2454","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS03125","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","Synpcc7942_0034","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","Synpcc7942_0413","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13375","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7942_RS09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Reactions","summary":"To be useful a metabolic model should consist at least of a few reactions.\nThis test simply checks if there are more than zero reactions.\n\nImplementation:\nCheck if the cobra.Model object has non-empty \"reactions\"\nattribute, this list is populated from the list of sbml:listOfReactions\nwhich should contain at least one sbml:reaction.","message":"1015 reactions are defined in the model.","data":["EX_gln__L_e","EX_hco3_e","EX_mn2_e","EX_arg__L_e","ADPT","O2tcx","AOXPBDC","DNTPPA","CBMD","BIOMASS_PIGMENTS","H2Otu_syn","DTMPK","BIOMASS__1","ORNTA","ATPM","ACOATA","5DOAN","3HAD160","RNDR3","Htex","G5SD","HISTDa","TRPS3","DMBZIDS2","HSTPT","ZCAROTDH2","ORNDC","GND","CMPA_1","U23GAAT2","HOXGfx","PGK","IMPD","LPOR","CHRPL","GCALDDy","MSBENZMT","DESAT18a","FUM","PHYFXOR","TMPPP_1","VPAMTr","RNDR1","TALA","GLYCL","ACONT","NDPK7","GTPCI","AIRC2","IGPS","MTAP","HEMEAS_1","DHORD3um","MTHFC","HBZNPT","GCATENEC","COCHL_1","HSDy","TRPS1","HISTDb","UPPDC1","GARFT","H4THDPR","UDPG4E","GLCS3","AICART","ASPTA","GLYOX","PRAGSr","SQD1","ACKr","UDCPDPS","GK1","SHKK","OXADC","G1PACT","3HAD60","PGI","KAS14","OHPBAT","PQH2tum","O2tu","O2tpp","H2Otex","SK_for_c","EX_mg2_e","3HAD80","3OAR160","NMNS","PPK","GALUi","PHYTES2_1","IGPDH","OMPDC","DCTPD","GLUSfx","NADS2","GLUTRR","G1PTT","UAMAGS","SPS","ADCL","CYTK1","DAPDC","PSIum","R05219","Cobalt2abcppI","PFK_3","THRS","NAMNPP","FOLD3","P5CR","MEHLER_1","ICHORS","3OAS140","PPK2","IPDPS_syn","GLYDHDA","SBP","H4THDPS","EAR60y","ZNabcpp","UAPGR","DHAD1","IPPS","ANS","SUCBZL","ADSL1r","NNATr","PERD","PPBNGS","ADOCBLS","LTHRK","PPS","APRAUR","PDS2_1","O2tex","ALAALAr","ADCPS2","GF6PTA","DNMPPA","PGMT","G5SADs","GLCP2_1","AGDI_1","LPADSS2","GLYCK","DPR","EX_ptrc_e","EAR120y","MAN1PT","NMNAT","TKT2","PSP_L","HEX7","PPNCL2","CHORS","CYTBD4cm","PPNCL3","CS","PPCDC","LDH_D","HPYRRy","ADMDC","PRE3BS","PPPGO2_1","BIOMASS_DNA","DMATT","DNAMTn2r","G3PD2","BIOMASS_CELL_WALL","PHYTES","RB15BPtcx","MI3PP","MOHMT","GLXO3r","FBA","RZ5PP","PROAKGOX1","ASAD","CYSS_2","LYCOPC","ACOTA","3HAD180","FTHFD","ALDD2y","3OAS80","PSCVT","CBPS","NTPP8","MEPCT","PDX5POi","DHAD2","DHFS","PGCD","SPMDabcpp","NTD6","NNDMBRT","PRATPP","ASNN","SERAT","PRAIS","PRAMPC","AMPMS3","G1PCTYT","ACBIPGT","SEPHCHCS","NMNDA","CA2abcpp","ORNTAC","SUCBZS","UHGADA2","DHNANT","ASPO6","HGYDAS","GGDPR","ASP1DC","PPNDH","ASPK","DXPS","ME2","3PGtcx","DDPGA","PAPSR","SADT","BIOMASS_COFACTORS","DPCOAK","NH4tpp","DM_h2_c","PC11M","DPOR","ARGSL","HSK","MTHFD","PMDPHT","ARGabcpp","3HAD140","ARGOXRum","DAPE","BCAROHX2","HPPK","PANTS","AHCi","G6PDH2r","ALAD_L","GTPCII","GLCBRAN3","DB4PS","DXPRIi","FBA3","RBFSa","GLUTRS","MPOMMM","METAT","EAR160y","DHORTS","PDX5PS2","KARI_23dhmp_1","ARGDC","GAPDi_nadp","NTD7","AIRC3","UMPK","ASPOb","RBFSb_1","SUCDum","FBP","CITCIb","MNabc_1","TMPK","AGPR","IPMD","CDPMEK","DVOCHR_1","H2CO3_NAt_syn","HEMEOS","PMANM","RPE","MPOMT_1","CPPPGO2","PC17M_1","UAMAS","GLUCYS","NDHPQRum","CYNL","DCTPD2","CYOOum","BPNT2","METS_1","PRUK","FNOR_1","GART","IPPMIb","DMTPHT","PC6YM_1","PGL","DDPA","ASPCT","HSERTA","OMCDC","CYRDAAT","MECDPDHf","Htcx","H2Otpp","HISTP","MTHFR3_1","EX_ca2_e","3HAD40_2","ZCAROTDH1","CYRDAR","BIOMASS_MEM_LIPIDS","HCO3tcx","GLYALDDy","IMPC","BIOMASS_PROTEIN","LDAPAT","EX_nh4_e","3OAR40_2","RNDR2","GRTT","NPDPS","3OAS100","ADSL2r","MAN6PI","HPROb","3OAS120","NTPP2","EAR180y","DHQTi","3OAS60","EAR40y","MG2uabcpp","KARA1","TKT1","PTRCabcpp","IPDDI","PKETF","ACODA","ENO","NDHPQRcm","NI2uabcpp","Kabcpp","TDPDRR","UAGCVT","TDPGDH","PRASCSi","PRFGS","MG2tex","GLU5K","TRDR","GLUPRT","PSERT","PC8XM","GMPS2","RBFK","NTRIRfx","UPP3MT","ACS","DHNCOAS","MCOATA","GTHPi","ARGSS","PKETX","PMPK","HMBS","PTPATi","PGLYCP","HTHRPDH","UAGAAT2","SPTc","GTHOr","TDPDRE","SHK3Dr","ORPT","PRPPS","CITMS","BCT1_syn","SPODM","TRDRf","AMPTASECG","SPRMS","PGAMT","NNDPR","ADSK","MECDPS","FCLT","SHCHCS3","PPA","ADCYRS","ATPPRT","CUabcpp","DHQS","GTHRDH_syn","ANPRT","PC6AR_1","ADK1","PRAIi","TRSARyr","CYNTtabcpp","RBPCcx","UPP3S","DHNPA_1","MOBDabcpp","NADK","BIOMASS_RNA","NADTRHD","PGM","FE3abcpp","DM_dialurate_c","CO2tex","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","EX_fe2_e","PQH2tcm","2PGLYCtcx","PDS1_1","EX_cu2_e","FRTT","3OAS180","EAR80y","DM_5drib_c","SK_amylose_c","EAR140y","EX_k_e","ACGS","CYTBD4um","DHPPDA","DHFR","BCAROHX","SK_14glucan_c","SK_glycogen_c","EX_h2o_e","EX_o2_e","EX_co2_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","EX_cobalt2_e","EX_no3_e","EX_zn2_e","EX_fe3_e","EX_so4_e","AFAT","EX_spmd_e","EX_mobd_e","DADK","G1SAT","EX_ni2_e","UAAGDS","HEX1","URIDK2r","CHPHYS","EX_na1_e","PIuabcpp","ARGDHpp","PHETA1","PFK","DMPPS_syn","ANS2","3OAS160","ACHBSb","PC20M","ADSS","THRPDC","MPOMOR_1","EX_cynt_e","IPPMIa","SPMS","EX_h_e","BPNT","ICDHyr","TMDS3","GLYOX_1","MTRI","CTPS2","FE3tex","GTHS","AHSERL2_1","PEPC","CHORM","NTRARf2","FE2tex","G6PDA","MPML","Nat_Kpp","PDH","TPI","E4PD","GAPD","CPPPGO","PRMICI","CAT","GLUR","OCBT","NI2tex","GLGC","PYK","CA2t2pp","ALAR","SULR_2","ADCS","UGMDDS","GLCDBRAN3","IG3PS","RPI","NAt3pp","MNtex","GLYCLTDx","FMNRy_1","GHMT2r","COBALT2tex","PGPP_OLE_PALM","CU2tex","MEOHtrpp","MEOHtex","H2Otcx","Zn2tex","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","DM_amob_c","ADNK1","OPMEACPD","OPMEACPR","EX_photon530_e","EX_photon550_e","SPP","SPMDtex","AGPAT160","EX_photon570_e","EX_photon590_e","EX_photon610_e","AGPATACP_HDE_PALM","LEUtex","BTS6","QUERT","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","HCO3tex","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","GLNtex","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","CYNTtex","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","ARGtex","GLUDGS_HDE_HDE","TYRTRS","DAGK160","MOBDtex","DAGK_HDE_PALM","DAGK161","NH4tex","SQDGS_PALM_PALM","SO4tex","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","PTRCtex","DGDGS_HDE_HDE","NO3tex","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","NAtex","PROTRS","GLYTRS","CYSTRS","CA2tex","ARGTRS","Ktex","TRPTRS","HISTRS","CO2tpp","PHETRS","EX_pi_e","ASNTRS","ASPTRS","UDPGLDC","PItex","AGTi","DBTS","THRTRS","LEUTRS","ILETRS","CHLADMT_1","LYSTRS","AOXSr2","AMAOTr","LIPOS2","ALATRS","TRNFE","VALTRS","FMETTRS","BACCL","BTNPL2","LIPAMPL_1","LIPOCT","LIPATPT_1","ZXANHX","PHOA410um","PHOA430um","CPH4S","OGMEACPR","CDGS","PHOA450um","PHOA470um","PHOA490um","CCGS","CDGR","PHOA510um","PHOA530um","PLYCOI","PHOA550um","SAMTRI","EPXQR","UPPRT","PHOA570um","PHOA590um","PHOA610um","ZCARDS","PHOA630um","PHOA650um","PHOA670um","UDPGD","GMAND","GFUCS","PHOA690um","NADDP","DM_pho_loss_c","ETCHLAS","ETBCARO","COLIPAabcex","MLDCP1App","CDPGLC46DH","AACPS6","ALDR18","ALDDC17","ALCD19","THZT","MLDCP1Bpp","PHYPQOX","MLDCP2App","MLDCP2Bpp","LALGP","AGM4Pt2pp","AGMt2pp","CXANHX","OGMEACPS","A5PISO","KDOPS","KDOPP","EX_meoh_e","NO2tex","KDOCT2","EGMEACPR","DXYTST","UAG2E","OANTS","ACGAMT","Htabcpp","ETAPCPSII","STCHLPSIum","DEXZEAX","PFOR","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","UAGPT3","GLYCOX1","UM4PL","UM3PL","PAPPT3","OANTIabcpp","OANTILpp","MDDCP1pp","MDDCP2pp","STACPSI","UDCPDP","MLTGY1pp","ETCPC","GLYCOX2","NO2tabcpp","MLTGY2pp","MLTGY3pp","MLTGY4pp","AGM4PA","FALGTHLs","CLtex","EX_cl_e","AM3PA","AM4PA","SK_fum_c","MALCOAMT","DM_succ_c","AGM3PApp","AGM4PApp","UM4PCP","SK_akg_c","MDRPD","NGAM_D1um","PSICRum","AM4PCP","4PCP","AGM4PCP","AGMH","PSIICRum","DM_ac_c","AGM3PH","DM_lac__D_c","ENOPH","NGAM","QULNS","AGM4PH","LADGMDH","ILETA","ALAGLUE","CELLSYN","ALAALAabcpp","LEUTA","ARD","VALTA","NDPK3","NDPK6","NDPK1","4PEPTabcpp","ALAALAD","ADPGLC","NDPK8","UNK3","NDPK5","DALAabcpp","NDPK4","ZISO","NDPK2","3OAR180","3OAR140","PAPA160","PHEOASE","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","ACGK","MCTP2App","MCTP1App","MCTP1Bpp","LEUabcpp","ACLSa","SULabcpp","PAPA_OLE_PALM","TYRTA","ACLSb","PHEOX_1","OPMEACPS","EAR100y","EHGLAT","KAS15","FALDH2","PHYTK","NDH_1_4_um_copy2","KARI_1","3HAD120","OGMEACPD","ACCOAC","ASPO5","PTHPS","CITCIa","DAGK_OLE_HDE","DAGK_OLE_PALM","3HAD100","PNTK","3OAR120","3OAR60","3OAR100","3OAR80","ALCD1","NDH_1_1_um_copy1","NDH_1_4_um_copy1","PCHLDA430","SFGTHi","PCHLDA650","GGCLUT2","SPR","OPAH","ACGAMK","AMANAPEr","AGDC","ANHMK","RNDR4","TRPS2","PSICSum","NAD_H2","PPND","CBFCum","ACM6PH","SUCR","CLt3_1pp","Ktu","THBTGT","FDH6","PCXHtpp","THISAT","PSIIum","ATPSum","CYSDES","NO3abcpp","GLNabcpp","GLNS","MDDEP1pp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","ASNS1","MDDCP3pp","MDDCP4pp","MDDCP5pp","MDDEP2pp","MDDEP3pp","MDDEP4pp","MNHNAtpp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX_glyc_e","EX_fuc__L_e","EX_glcur_e","EX_glcn_e","EX_glyc3p_e","EX_xyl__D_e","EX_lac__L_e","EX_g6p_e","EX_malt_e","EX_melib_e","EX_thymd_e","EX_galctn__D_e","EX_rib__D_e","EX_rmn_e","EX_fru_e","EX_ac_e","EX_glc__D_e","EX_asn__L_e","EX_sucr_e","EX_uri_e","EX_12ppd__S_e","EX_akg_e","EX_lcts_e","EX_malttr_e","EX_dad_2_e","EX_adn_e","EX_g1p_e","EX_f6p_e","EX_ins_e","EX_cit_e","EX_inost_e","EX_fum_e","EX_ppa_e","EX_galct__D_e","EX_glyclt_e","EX_mal__D_e","EX_mal__L_e","EX_ser__L_e","EX_thr__L_e","EX_ala__L_e","EX_acac_e","EX_acmana_e","EX_galur_e","EX_peamn_e","EX_etha_e","EX_tym_e","EX_lyx__L_e","EX_pyr_e","EX_galctn__L_e","EX_acnam_e","EX_all__D_e","EX_4abut_e","EX_but_e","EX_dca_e","EX_5dglcn_e","EX_hxa_e","EX_tartr__L_e","EX_lys__L_e","EX_met__L_e","EX_gly_e","EX_his__L_e","EX_hom__L_e","EX_ile__L_e","EX_orn_e","EX_phe__L_e","EX_val__L_e","EX_dha_e","EX_cys__L_e","EX_no2_e","EX_urea_e","EX_trp__L_e","EX_tyr__L_e","EX_agm_e","EX_acgal_e","EX_gam_e","EX_ura_e","EX_ade_e","EX_cytd_e","EX_csn_e","EX_gua_e","EX_gsn_e","EX_thym_e","EX_xan_e","EX_xtsn_e","EX_alltn_e","EX_23camp_e","EX_3amp_e","EX_gmp_e","EX_23cgmp_e","EX_3gmp_e","EX_cmp_e","EX_23ccmp_e","EX_gam6p_e","EX_3cmp_e","EX_ump_e","EX_23cump_e","EX_man6p_e","EX_pser__L_e","EX_thrp_e","EX_3ump_e","EX_tyrp_e","EX_minohp_e","SUCRt2","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","MDH","FNOR","PC6YM","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE10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Metabolites","summary":"To be useful a metabolic model should consist at least of a few\nmetabolites that are converted by reactions.\nThis test simply checks if there are more than zero metabolites.\n\nImplementation:\nCheck if the cobra.Model object has non-empty\n\"metabolites\" attribute, this list is populated from the list of\nsbml:listOfSpecies which should contain at least one sbml:species.","message":"924 metabolites are defined in the 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Since it may be\ndifficult to obtain formulas for certain metabolites this test serves as a\nmere report. Models can still be stoichiometrically consistent even\nwhen chemical formulas are not defined for each metabolite.\n\nImplementation:\nCheck if each cobra.Metabolite has a non-empty \"formula\"\nattribute. This attribute is set by the parser if there is an\nfbc:chemicalFormula attribute for the corresponding species in the\nSBML.","message":"There are a total of 140         metabolites (15.15%) without a\nformula: bm_pigm_c, bm_pro_c, bm_cofactors_c, bm_carbs_c, bm_cw_c, ...","data":["bm_pigm_c","bm_pro_c","bm_cofactors_c","bm_carbs_c","bm_cw_c","bm_rna_c","bm_memlip_c","bm_dna_c","icolipacy_c","icolipacy_p","oanticy_c","oanticy_p","colipacy_p","colipacy_e","tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c"],"format_type":"count","metric":0.15151515151515152},"test_metabolites_charge_presence":{"duration":0.00024665999995932,"result":"passed","title":"Metabolites without Charge","summary":"To be able to ensure that reactions are charge-balanced, all model\nmetabolites ought to be provided with a charge. Since it may be\ndifficult to obtain charges for certain metabolites this test serves as a\nmere report. Models can still be stoichiometrically consistent even\nwhen charge information is not defined for each metabolite.\n\nImplementation:\nCheck if each cobra.Metabolite has a non-empty \"charge\"\nattribute. This attribute is set by the parser if there is an\nfbc:charge attribute for the corresponding species in the\nSBML.","message":"There are a total of 0         metabolites (0.00%) without a charge:","data":[],"format_type":"count","metric":0.0},"test_gene_protein_reaction_rule_presence":{"duration":0.003179690000024493,"result":"failed","title":"Reactions without GPR","summary":"Gene-Protein-Reaction rules express which gene has what function.\nThe presence of this annotation is important to justify the existence\nof reactions in the model, and is required to conduct in silico gene\ndeletion studies. However, reactions without GPR may also be valid:\nSpontaneous reactions, or known reactions with yet undiscovered genes\nlikely lack GPR.\n\nImplementation:\nCheck if each cobra.Reaction has a non-empty\n\"gene_reaction_rule\" attribute, which is set by the parser if there is an\nfbc:geneProductAssociation defined for the corresponding reaction in the\nSBML.","message":"There are a total of 146 reactions (14.38%) without GPR:         DRBK,\nPHOA690um, FA80ACPHi, FALGTHLs, H2Otu_syn, ...","data":["DRBK","PHOA690um","FA80ACPHi","FALGTHLs","H2Otu_syn","FACOAE100","MOCOS","TRNFE","FACOAE120","AMAA","USHD2","FACOAE140","GLXO3r","CYNTtex","FACOAE160","FE2tex","ETBCARO","ETCHLAS","NAtex","FACOAE161","Zn2tex","APRAUR","FACOAE180","BIOMASS__1","BIOMASS_MEM_LIPIDS","DNMPPA","SO4tex","5DOAN","RB15BPtcx","BIOMASS_CARB","RZ5PP","PHOA550um","AGM4Pt2pp","FACOAE181","ATPM","MLDCP1App","PItex","NGAM_D1um","FACOAE80","CLtex","DPGM","2PGLYCtcx","MOADSUx","FACOAL100i","PHOA610um","NO2tex","FACOAL120i","HCO3tex","Htcx","PHOA410um","ADNK1","MPTS","MOBDtex","FACOAL140i","BIOMASS_PROTEIN","ETAPCPSII","H2Otex","HCO3tcx","Ktex","OMCDC","CYRDAR","PSICRum","BIOMASS_CELL_WALL","FACOAL160i","O2tcx","O2tex","MPTAT","GUACYC","CO2tex","LEUtex","3PGtcx","PHOA570um","FACOAL161i","RDXRr","CBMD","NH4tex","MPTSS","G5SADs","MNtex","PHOA630um","DNTPPA","PHOA590um","FA100ACPHi","MEOHtrpp","CHLADMT_1","FACOAL180i","PHOA430um","CPMPS","MLDCP2App","FA120ACPHi","PHOA490um","HISTP","CA2tex","FACOAL181i","ARGtex","GTPC","STCHLPSIum","PQH2tum","FA140ACPHi","AOXPBDC","PHOA510um","BIOMASS_RNA","Htex","PHOA670um","MDH","MLDCP1Bpp","FACOAL80i","MEOHtex","SPMDtex","H2Otpp","COLIPAabcex","BIOMASS_COFACTORS","COBALT2tex","FA160ACPHi","PHOA650um","GLCP4","NO3tex","FE3tex","FA161ACPHi","CYSTL","PSIICRum","PHOA530um","O2tpp","NI2tex","O2tu","Htabcpp","H2Otcx","GLCP3","GLNtex","CU2tex","CSND","FA180ACPHi","PGPP_OLE_PALM","MLDCP2Bpp","BIOMASS_PIGMENTS","G1Dx","PQH2tcm","PHOA450um","DEXZEAX","AGMt2pp","FA181ACPHi","PTRCtex","NGAM","DRPA","CO2tpp","PHOA470um"],"format_type":"count","metric":0.1438423645320197},"test_ngam_presence":{"duration":0.1492778320000525,"result":"passed","title":"Non-Growth Associated Maintenance Reaction","summary":"The Non-Growth Associated Maintenance reaction (NGAM) is an\nATP-hydrolysis reaction added to metabolic models to represent energy\nexpenses that the cell invests in continuous processes independent of\nthe growth rate. Memote tries to infer this reaction from a list of\nbuzzwords, and the stoichiometry and components of a simple ATP-hydrolysis\nreaction.\n\nImplementation:\nFrom the list of all reactions that convert ATP to ADP select the reactions\nthat match the irreversible reaction \"ATP + H2O -> ADP + HO4P + H+\",\nwhose metabolites are situated within the main model compartment.\nThe main model compartment is assumed to be the cytosol, yet, if that\ncannot be identified, it is assumed to be the compartment with the most\nmetabolites. The resulting list of reactions is then filtered further by\nattempting to match the reaction name with any of the following buzzwords\n('maintenance', 'atpm', 'requirement', 'ngam', 'non-growth', 'associated').\nIf this is possible only the filtered reactions are returned, if not the\nlist is returned as is.","message":"A total of 1 NGAM reactions could be identified:         ATPM","data":["ATPM"],"format_type":"count","metric":0.0},"test_metabolic_coverage":{"duration":0.0001814290000083929,"result":"passed","title":"Metabolic Coverage","summary":"The degree of metabolic coverage indicates the modeling detail of a\ngiven reconstruction calculated by dividing the total amount of\nreactions by the amount of genes. Models with a 'high level of modeling\ndetail have ratios >1, and models with a low level of detail have\nratios <1. This difference arises as models with basic or intermediate\nlevels of detail are assumed to include many reactions in which several\ngene products and their enzymatic transformations are ‘lumped’.\n\nImplementation:\nDivides the amount reactions by the amount of genes. Raises an error\nif the model does not contain either reactions or genes.","message":"The degree of metabolic coverage is 1.2.","data":[1015,882],"format_type":"percent","metric":1.1507936507936507},"test_compartments_presence":{"duration":0.0005716580000125759,"result":"passed","title":"Total Compartments","summary":"While simplified metabolic models may be perfectly viable, generally\nacross the tree of life organisms contain at least one distinct\ncompartment: the cytosol or cytoplasm. In the case of prokaryotes there is\nusually a periplasm, and eurkaryotes are more complex. In addition to the\ninternal compartment, a metabolic model also reflects the extracellular\nenvironment i.e. the medium/ metabolic context in which the modelled cells\ngrow. Hence, in total, at least two compartments can be expected from a\nmetabolic model.\n\nImplementation:\nCheck if the cobra.Model object has a non-empty \"compartments\"\nattribute, this list is populated from the list of sbml:listOfCompartments\nwhich should contain at least two sbml:compartment elements.","message":"A total of 7 compartments are defined in the model: c, cx, u, um, cm,\n...","data":["c","cx","u","um","cm","p","e"],"format_type":"count","metric":0.0},"test_protein_complex_presence":{"duration":0.017048606999992444,"result":"passed","title":"Enzyme Complexes","summary":"Based on the gene-protein-reaction (GPR) rules, it is possible to infer\nwhether a reaction is catalyzed by a single gene product, isozymes or by a\nheteromeric protein complex. This test checks that at least one\nsuch heteromeric protein complex is defined in any GPR of the model. For\nS. cerevisiae it could be shown that \"essential proteins tend to [cluster]\ntogether in essential complexes\"\n(https://doi.org/10.1074%2Fmcp.M800490-MCP200).\n\nThis might also be a relevant metric for other organisms.\n\nImplementation:\nIdentify GPRs which contain at least one logical AND that combines two\ndifferent gene products.","message":"A total of 93 reactions are catalyzed by complexes defined\nthrough GPR rules in the model.","data":["TRPS3","ZCAROTDH2","GLYCL","COCHL_1","TRPS1","PSIum","Cobalt2abcppI","MEHLER_1","ZNabcpp","ANS","LPADSS2","CYTBD4cm","BIOMASS_DNA","CBPS","DHNANT","DPOR","ARGabcpp","SUCDum","CITCIb","MNabc_1","CYOOum","IPPMIb","ASPCT","Kabcpp","PRFGS","BCT1_syn","TRDRf","ATPPRT","CYNTtabcpp","RBPCcx","MOBDabcpp","NADTRHD","FE3abcpp","NPHBDC","CYTBD4um","PIuabcpp","ANS2","ACHBSb","IPPMIa","MPML","Nat_Kpp","PDH","GLCDBRAN3","IG3PS","GLYCLTDx","BTS6","G3PAT160","G3PAT161","G3PAT1819Z_1","GLNTRS","GLYTRS","PHETRS","LIPOS2","OANTS","ICLIPAS","MOAT_1","MPTG","MPTG2","OANTIabcpp","OANTILpp","ETCPC","NO2tabcpp","CELLSYN","ALAALAabcpp","4PEPTabcpp","DALAabcpp","LEUabcpp","ACLSa","SULabcpp","ACLSb","NDH_1_4_um_copy2","ACCOAC","CITCIa","NDH_1_1_um_copy1","NDH_1_4_um_copy1","TRPS2","PSICSum","NAD_H2","CBFCum","CLt3_1pp","THISAT","PSIIum","ATPSum","CYSDES","NO3abcpp","GLNabcpp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","ASNS1","MNHNAtpp","FNOR"],"format_type":"count","metric":0.0916256157635468},"test_find_pure_metabolic_reactions":{"duration":0.0069518659999516785,"result":"passed","title":"Purely Metabolic Reactions","summary":"If a reaction is neither a transport reaction, a biomass reaction nor a\nboundary reaction, it is counted as a purely metabolic reaction. This test\nrequires the presence of metabolite formula to be able to identify\ntransport reactions. This test is passed when the model contains at least\none purely metabolic reaction i.e. a conversion of one metabolite into\nanother.\n\nImplementation:\nFrom the list of all reactions, those that are boundary, transport and\nbiomass reactions are removed and the remainder assumed to be pure\nmetabolic reactions. Boundary reactions are identified using the attribute\ncobra.Model.boundary. Please read the description of \"Transport Reactions\"\nand \"Biomass Reaction Identified\" to learn how they are identified.","message":"A total of 706 (69.56%) purely metabolic reactions are defined in\nthe model, this excludes transporters, exchanges, or pseudo-reactions:\nDRBK, SPP, CHORM, SHK3Dr, DBTS, ...","data":["DRBK","SPP","CHORM","SHK3Dr","DBTS","NAD_H2","TKT1","MOCOS","PRE3BS","THII","UPP3S","PERD","AIRC2","SHS1","AIRC3","NTRARf2","PRUK","UMPK","ASPOb","PPCDC","NTRIRfx","CS","PPA","ILETA","PNTK","3HAD80","UAPGR","NTPP2","RBFK","RBFSb_1","ALAGLUE","3OAR120","AOXSr2","PPK2","CELLSYN","3OAS140","CYTK1","AGTi","3OAR60","ATPPRT","PRPPS","FBP","ADCYRS","GALUi","ORPT","THRTRS","PPND","3OAR100","3OAR160","NADK","PDH","LDH_D","MPOMC1_1","VALTA","ADNK1","MPTS","CITCIb","3OAS120","LEUTA","3OAR80","GAPD","ERTHMMOR","OPMEACPD","DMBZIDS2","DAPDC","IPDPS_syn","TRPS3","LEUTRS","ADCPS2","PPK","ALCD1","FRTT","TPI","ALAALAr","VALTRS","ADOCBLS","UPP3MT","ILETRS","NMNS","PPBNGS","E4PD","NDH_1_1_um_copy1","HPYRRy","CITMS","OPMEACPR","3OAS180","FDH6","CHLADMT_1","GLYDHDA","TMPK","ARD","NDH_1_4_um_copy1","FNOR_1","THBTGT","ADMDC","R05219","FMETTRS","H4THDPS","PDS1_1","HSTPT","SBP","CPPPGO","NDPK3","DCTPD","IPMD","AMAOTr","LTHRK","CAT","ORNDC","NDPK6","CDPMEK","AGPAT160","DHQS","GGCLUT2","THISAT","EAR180y","NDPK1","ZCAROTDH2","AGPR","NDPK8","LIPOS2","IGPDH","ANPRT","PYK","PPS","PRMICI","SPR","PHYTES2_1","ACM6PH","ALATRS","AFAT","OPAH","AGPATACP_HDE_PALM","SPODM","GTHRDH_syn","DVOCHR_1","PFK_3","ALAALAD","ARGSS","NDH_1_1_um_copy2","GLUR","METS_1","TDPDRR","AMPTASECG","QUERT","EAR140y","OMPDC","BTS6","OCBT","PPPGO2_1","TRNFE","DADK","HEX1","HMBS","EAR60y","3OAS60","MDDCP4pp","EPMEACPR","PKETF","EAR80y","IPDDI","USHD2","PMEACPE","HEMEOS","ADPGLC","RPE","DHQTi","IPPMIb","GLGC","NAMNPP","CPH4S","CMPA_1","PMANM","DHNPA_1","ACS","PC17M_1","BACCL","G1SAT","TRDRf","APRAUR","G3PAT160","UNK3","MDDCP5pp","ADK1","SPMS","NDPK5","DNMPPA","PC6AR_1","NDPK2","DMATT","BTNPL2","GND","MPOMT_1","NADS2","ALAR","PDS2_1","SUCR","SULR_2","G1PTT","GLUSfx","LIPAMPL_1","TDPGDH","ADCS","DPGM","DMTPHT","CPPPGO2","DHNCOAS","NDPK4","MOADSUx","MAN6PI","DHNCOAT","AGPATACP_OLE_HDE","NPDPS","LIPOCT","UAAGDS","GLUDGE_HDE_HDE","GART","PRAIi","SPRMS","LIPATPT_1","U23GAAT2","UGMDDS","HTHRPDH","RBPCcx","MCTP2App","PGLYCP","ARGDHpp","G3PD2","NNDPR","3OAR180","BPNT","IMPD","SHCHCS3","CDGR","G3PAT161","KARA1","GLCDBRAN3","ZXANHX","PRFGS","NPHBDC","ASNS1","ZISO","MDDCP3pp","PGAMT","THRS","SFGTHi","TDPDRE","MDDEP2pp","MPTAT","TRSARyr","ACGS","IG3PS","GLUTRR","ADSL1r","LPOR","UAGCVT","ACGAMK","PLYCOI","HOXGfx","URIDK2r","GLUDGE_OLE_PALM","GLCP2_1","G3PAT1819Z_1","MPTSS","G5SADs","AGDI_1","MECDPDHf","BCAROHX","IPPS","3OAS100","RPI","GLUDGS_HDE_HDE","AMANAPEr","CHPHYS","3OAR140","CPMPS","DNAMTn2r","ENO","IPPMIa","ICHORS","GLNS","MCOATA","MEHLER_1","GTHOr","GLUDGE_OLE_HDE","AGDC","MDDEP3pp","GTPC","ANHMK","EAR40y","PAPA160","ADCL","PGK","DHPPDA","P5CR","FMNRy_1","OGMEACPR","AGPATACP_OLE_PALM","MDH","GF6PTA","SAMTRI","FOLD3","SPTc","CCGS","MDDEP4pp","DHAD1","UAGAAT2","ADSK","PHEOASE","PHETA1","CYSDES","PGMT","HPROb","RNDR4","FNOR","GLUDGS_OLE_PALM","CDGS","LPADSS2","MDDEP1pp","CYSTL","GHMT2r","PAPA_HDE_PALM","FCLT","GLUDGE_HDE_PALM","PC6YM","ANS","ADSL2r","MECDPS","PGM","ACODA","TRPS2","DESAT16a","CSND","MOHMT","UAGDP","PGPP_OLE_PALM","GLUDGS_HDE_PALM","SPS","PAPA161","G1Dx","AGPAT161","ACGK","NNATr","DHFR","PAPA_OLE_HDE","MOGDS","GTHPi","UAMAGS","PRASCSi","DRPA","PROAKGOX1","SUCBZL","LYCBC1","GLUDGS_OLE_HDE","MTAP","EGMEACPR","MDDCP1pp","GCALDDy","AMAA","PTPATi","GLXO3r","MTHFD","MCTP1App","PRATPP","KDOCT2","MAN1PT","MDDCP2pp","MCTP1Bpp","ASNN","PHEOX_1","CHRPL","MLTGY1pp","ARGSL","SERAT","TYRTRS","STACPSI","EPXQR","PFK","AICART","KDOPS","FBA","KDOPP","RZ5PP","PRAIS","AMPMS3","ASPTA","DMPPS_syn","HSK","ASAD","PRAMPC","ACLSa","MSBENZMT","DAGK161","DAGK160","HEMEAS_1","ETCPC","GLYCOX2","PMDPHT","PKETX","PMPK","GLYOX","GLYCK","UPPRT","PHYFXOR","MLTGY2pp","G1PCTYT","BCAROHX2","ACBIPGT","DXYTST","3OAR40_2","ADPT","ETAPCPSII","DAGK_HDE_PALM","3HAD140","GUACYC","DESAT18a","PRAGSr","UAG2E","EAR120y","ANS2","MLTGY4pp","PAPSR","RDXRr","CBMD","DAPE","PAPA_OLE_PALM","SEPHCHCS","DNTPPA","FA100ACPHi","MLTGY3pp","ZCAROTDH1","DDPA","CYRDAAT","OANTS","MTHFC","DPR","ACGAMT","NMNDA","FA120ACPHi","SQDGS_PALM_PALM","FUM","LYCOPC","PGPS_OLE_PALM","STCHLPSIum","ACLSb","EAR100y","FA140ACPHi","AOXPBDC","3OAS160","OPMEACPS","ACKr","SQDGS_HDE_PALM","SQD1","FA160ACPHi","ORNTAC","HPPK","UDPGD","BPNT2","HBZNPT","UDCPDPS","FA161ACPHi","GRTT","DGDGS_HDE_PALM","SUCBZS","CYSS_2","FA180ACPHi","NADTRHD","TYRTA","GMAND","PANTS","PC20M","HSERTA","DEXZEAX","UHGADA2","AGM4PA","FA181ACPHi","GCATENEC","ACOTA","TRDR","ACHBSb","GFUCS","AHCi","CYNL","ASPCT","DHNANT","FA80ACPHi","FALGTHLs","DGDGS_HDE_HDE","TMPPP_1","DGDGS_OLE_PALM","PFOR","FACOAE100","VPAMTr","ASPO6","GLYTRS","G6PDH2r","ACMAMT","COCHL_1","GLU5K","DGDGS_OLE_HDE","AM3PA","FACOAE120","PHYTES","3HAD180","THRPDC","PROTRS","GGDPR","ALAD_L","RNDR2","EHGLAT","NMNAT","HGYDAS","ADSS","DTMPK","DDPGA","FACOAE140","HCO3E_1_cx","NADDP","GTPCII","CDPDAGS_OLE_PALM","GK1","KAS15","HSDy","PDX5POi","FACOAE160","OGMEACPS","ETBCARO","ICLIPAS","AGM4PApp","ETCHLAS","FALDH2","FACOAE161","GLCBRAN3","SERTRS","OGMEACPD","MTHFR3_1","GLNTRS","RNDR1","HEX7","ICDHyr","FTHFD","MPOMOR_1","FACOAE180","SHKK","GLUPRT","ASP1DC","MOAT_1","PHYTK","PSP_L","DB4PS","5DOAN","METTRS","UDCPDP","AGM3PApp","AGM4PH","TMDS3","3HAD160","ALDD2y","FACOAE181","PSERT","ATPM","ASPK","MLDCP1App","MI3PP","FBA3","NDH_1_4_um_copy2","PPNDH","DXPRIi","LDAPAT","HISTDb","TKT2","FACOAE80","3OAS80","UM4PCP","TRPS1","OXADC","CDPGLC46DH","TALA","KARI_1","FACOAL100i","ORNTA","AACPS6","PSCVT","MPML","FACOAL120i","AM4PCP","G1PACT","DXPS","ALDR18","RBFSa","GLYCL","UDPG4E","CBPS","UM4PL","MDRPD","FACOAL140i","QULNS","ME2","GLUTRS","OMCDC","CYRDAR","NTPP8","FACOAL160i","ALDDC17","ACCOAC","ARGTRS","MPOMMM","UAGPT3","GLYOX_1","CYSTRS","ASPO5","FACOAL161i","3HAD60","ALCD19","PTHPS","PPNCL2","G6PDA","ACONT","MEPCT","AHSERL2_1","GARFT","PC11M","SADT","PC6YM_1","METAT","UPPDC1","3HAD40_2","4PCP","CITCIa","FACOAL180i","AGM3PH","GLYCOX1","MLDCP2App","HISTP","THZT","PGI","GLYCLTDx","FACOAL181i","ASNTRS","AGM4PCP","CHORS","EAR160y","DAGK_OLE_PALM","HISTDa","KAS14","IGPS","ACOATA","PHETRS","MLDCP1Bpp","AM4PA","FACOAL80i","DHAD2","MTRI","UM3PL","3HAD100","DHORTS","AGMH","DCTPD2","GLCP4","RNDR3","GLUCYS","PEPC","NTD6","GMPS2","CTPS2","G5SD","DHFS","DPOR","HISTRS","LADGMDH","PPNCL3","DPCOAK","NTD7","PAPPT3","PSIICRum","GTPCI","PDX5PS2","IMPC","GLCS3","PC8XM","A5PISO","GAPDi_nadp","TRPTRS","PGL","ASPTRS","GLCP3","PGCD","H4THDPR","UDPGLDC","LALGP","ENOPH","KARI_23dhmp_1","MLDCP2Bpp","MALCOAMT","UAMAS","CXANHX","NNDMBRT","GLYALDDy","DAGK_OLE_HDE","NDPK7","LYSTRS","OANTILpp","3HAD120","GTHS","OHPBAT","ARGDC"],"format_type":"count","metric":0.6955665024630542},"test_find_constrained_pure_metabolic_reactions":{"duration":0.0025759920000041348,"result":"passed","title":"Purely Metabolic Reactions with Constraints","summary":"If a reaction is neither a transport reaction, a biomass reaction nor a\nboundary reaction, it is counted as a purely metabolic reaction. This test\nrequires the presence of metabolite formula to be able to identify\ntransport reactions. This test simply reports the number of purely\nmetabolic reactions that have fixed constraints and does not have any\nmandatory 'pass' criteria.\n\nImplementation: From the pool of pure metabolic reactions identify\nreactions which are constrained to values other than the model's minimal or\nmaximal possible bounds.","message":"A total of 11 (1.56%) purely metabolic reactions have fixed\nconstraints in the model, this excludes transporters, exchanges, or\npseudo-reactions: 0.0 <= NDH_1_1_um_copy2 <= 0.0, -1000.0 <= IPPMIb <=\n0.0, 0.0 <= CPPPGO2 <= 0.0, -1000.0 <= KARA1 <= 0.0, -1000.0 <= IPPMIa\n<= 0.0, ...","data":["0.0 <= NDH_1_1_um_copy2 <= 0.0","-1000.0 <= IPPMIb <= 0.0","0.0 <= CPPPGO2 <= 0.0","-1000.0 <= KARA1 <= 0.0","-1000.0 <= IPPMIa <= 0.0","-1000.0 <= ASAD <= 0.0","-1000.0 <= HSDy <= 0.0","0.0 <= NDH_1_4_um_copy2 <= 0.0","-1000.0 <= LDAPAT <= 0.0","-1000.0 <= GLYCLTDx <= 0.0","0.0 <= DPOR <= 0.0"],"format_type":"count","metric":0.015580736543909348},"test_find_transport_reactions":{"duration":0.0002473220000069887,"result":"passed","title":"Transport Reactions","summary":"Cellular metabolism in any organism usually involves the transport of\nmetabolites across a lipid bi-layer. This test reports how many\nof these reactions, which transports metabolites from one compartment\nto another, are present in the model, as at least one transport reaction\nmust be present for cells to take up nutrients and/or excrete waste.\n\nImplementation:\nA transport reaction is defined as follows:\n1. It contains metabolites from at least 2 compartments and\n2. at least 1 metabolite undergoes no chemical reaction, i.e.,\nthe formula and/or annotation stays the same on both sides of the equation.\n\nA notable exception is transport via PTS, which also contains the following\nrestriction:\n3. The transported metabolite(s) are transported into a compartment through\nthe exchange of a phosphate.\n\nAn example of transport via PTS would be\npep(c) + glucose(e) -> glucose-6-phosphate(c) + pyr(c)\n\nReactions similar to transport via PTS (referred to as \"modified transport\nreactions\") follow a similar pattern:\nA(x) + B-R(y) -> A-R(y) + B(y)\n\nSuch modified transport reactions can be detected, but only when the\nformula is defined for all metabolites in a particular reaction. If this\nis not the case, transport reactions are identified through annotations,\nwhich cannot detect modified transport reactions.","message":"A total of 123 (12.12%) transport reactions are defined in the\nmodel, this excludes purely metabolic reactions, exchanges, or\npseudo-reactions: PHOA690um, H2Otu_syn, H2CO3_NAt_syn, ICLIPAabcpp,\nCYNTtex, ...","data":["PHOA690um","H2Otu_syn","H2CO3_NAt_syn","ICLIPAabcpp","CYNTtex","CLt3_1pp","FE2tex","ZNabcpp","MG2tex","FE3abcpp","NAtex","Zn2tex","CUabcpp","CA2t2pp","PCHLDA430","MOBDabcpp","SO4tex","LEUabcpp","RB15BPtcx","NDHPQRcm","PHOA550um","AGM4Pt2pp","Nat_Kpp","PItex","DALAabcpp","NGAM_D1um","SUCDum","Cobalt2abcppI","CLtex","SUCRt2","MNHNAtpp","ALAALAabcpp","2PGLYCtcx","ATPSum","NDHPQRum","PHOA610um","MPTG","NO2tex","HCO3tex","Htcx","PHOA410um","CYTBD4um","CYTBD4cm","MG2uabcpp","MOBDtex","ARGabcpp","SULabcpp","H2Otex","HCO3tcx","Ktex","PSICRum","MPTG2","O2tcx","NH4tpp","O2tex","DHORD3um","CO2tex","LEUtex","ARGOXRum","3PGtcx","PHOA570um","MNabc_1","PHYPQOX","NH4tex","PSIum","Ktu","MNtex","PHOA630um","PHOA590um","MEOHtrpp","PHOA430um","ZCARDS","CYNTtabcpp","PHOA490um","CA2tex","BCT1_syn","ARGtex","PQH2tum","PHOA510um","Htex","CA2abcpp","PHOA670um","MEOHtex","SPMDtex","NAt3pp","H2Otpp","COLIPAabcex","CO2tpp","Kabcpp","PIuabcpp","COBALT2tex","CYOOum","PCHLDA650","PCXHtpp","PHOA650um","NO3abcpp","NO3tex","FE3tex","NO2tabcpp","PHOA530um","PTRCabcpp","O2tpp","NI2tex","O2tu","Htabcpp","H2Otcx","PSIIum","GLNtex","CU2tex","PSIICSum","NI2uabcpp","PQH2tcm","PHOA450um","OANTIabcpp","4PEPTabcpp","AGMt2pp","GLNabcpp","PSICSum","PTRCtex","NGAM","SPMDabcpp","CBFCum","PHOA470um"],"format_type":"count","metric":0.12118226600985221},"test_find_constrained_transport_reactions":{"duration":0.0004616119999809598,"result":"passed","title":"Transport Reactions with Constraints","summary":"Cellular metabolism in any organism usually involves the transport of\nmetabolites across a lipid bi-layer. Hence, this test reports how many\nof these reactions, which transports metabolites from one compartment\nto another, have fixed constraints. This test does not have any mandatory\n'pass' criteria.\n\nImplementation:\nPlease refer to \"Transport Reactions\" for details on how memote identifies\ntransport reactions.\nFrom the pool of transport reactions identify reactions which are\nconstrained to values other than the model's median lower and upper bounds.","message":"A total of 0 (0.00%) transport reactions have fixed\nconstraints in the model:","data":[],"format_type":"count","metric":0.0},"test_transport_reaction_gpr_presence":{"duration":0.0007156870000244453,"result":"failed","title":"Fraction of Transport Reactions without GPR","summary":"As it is hard to identify the exact transport processes within a cell,\ntransport reactions are often added purely for modeling purposes.\nHighlighting where assumptions have been made versus where\nthere is proof may help direct the efforts to improve transport and\ntransport energetics of the tested metabolic model.\nHowever, transport reactions without GPR may also be valid:\nDiffusion, or known reactions with yet undiscovered genes likely lack GPR.\n\nImplementation:\nCheck which cobra.Reactions classified as transport reactions have a\nnon-empty \"gene_reaction_rule\" attribute.","message":"There are a total of 66 transport reactions (53.66% of all\ntransport reactions) without GPR:         PHOA690um, H2Otu_syn,\nCYNTtex, FE2tex, NAtex, ...","data":["PHOA690um","H2Otu_syn","CYNTtex","FE2tex","NAtex","Zn2tex","SO4tex","RB15BPtcx","PHOA550um","AGM4Pt2pp","PItex","NGAM_D1um","CLtex","2PGLYCtcx","PHOA610um","NO2tex","HCO3tex","Htcx","PHOA410um","MOBDtex","H2Otex","HCO3tcx","Ktex","PSICRum","O2tcx","O2tex","CO2tex","LEUtex","3PGtcx","PHOA570um","NH4tex","MNtex","PHOA630um","PHOA590um","MEOHtrpp","PHOA430um","PHOA490um","CA2tex","ARGtex","PQH2tum","PHOA510um","Htex","PHOA670um","MEOHtex","SPMDtex","H2Otpp","COLIPAabcex","CO2tpp","COBALT2tex","PHOA650um","NO3tex","FE3tex","PHOA530um","O2tpp","NI2tex","O2tu","Htabcpp","H2Otcx","GLNtex","CU2tex","PQH2tcm","PHOA450um","AGMt2pp","PTRCtex","NGAM","PHOA470um"],"format_type":"percent","metric":0.5365853658536586},"test_find_reversible_oxygen_reactions":{"duration":0.023461967000002915,"result":"passed","title":"Number of Reversible Oxygen-Containing Reactions","summary":"The directionality of oxygen-producing/-consuming reactions affects the\nmodel's ability to grow anaerobically i.e. create faux-anaerobic organisms.\nThis test reports how many of these oxygen-containing reactions are\nreversible. This test does not have any mandatory 'pass' criteria.\n\nImplementation:\nFirst, find the metabolite representing atmospheric oxygen in the model on\nthe basis of an internal mapping table or by specifically looking for the\nformula \"O2\". Then, find all reactions that produce or consume oxygen and\nreport those that are reversible.","message":"There are a total of 8 reversible oxygen-containing reactions\n(19.05% of all oxygen-containing reactions): O2tex, DESAT18a, O2tpp,\nO2tu, GLXO3r, ...","data":["O2tex","DESAT18a","O2tpp","O2tu","GLXO3r","DESAT16a","PDX5POi","EX_o2_e"],"format_type":"count","metric":0.19047619047619047},"test_find_unique_metabolites":{"duration":0.11695432200002642,"result":"passed","title":"Unique Metabolites","summary":"Metabolites may be transported into different compartments, which means\nthat in a compartimentalized model the number of metabolites may be\nmuch higher than in a model with no compartments. This test counts only\none occurrence of each metabolite and returns this as the number of unique\nmetabolites. The test expects that the model is compartimentalized, and\nthus, that the number of unique metabolites is generally lower than the\ntotal number of metabolites.\n\nImplementation:\nReduce the list of metabolites to a unique set by removing the compartment\ntag. The cobrapy SBML parser adds compartment tags to each metabolite ID.","message":"Not counting the same entities in other compartments, there is a\ntotal of 784 (84.85%) unique metabolites in the model: sheme, glx,\nalaala, tyr__L, epxqtrna, 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Metabolites in Identical Compartments","summary":"The main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical metabolites from different namespaces\n(hence different IDs). This test therefore expects that every metabolite\nin any particular compartment has unique inchikey values.\n\nImplementation:\nIdentifies duplicate metabolites in each compartment by\ndetermining if any two metabolites have identical InChI-key annotations.\nFor instance, this function would find compounds with IDs ATP1 and ATP2 in\nthe cytosolic compartment, with both having the same InChI annotations.","message":"There are a total of 0 metabolites in the model which         have\nduplicates in the same compartment:","data":[],"format_type":"count","metric":0.0},"test_find_reactions_with_partially_identical_annotations":{"duration":0.12067904900004578,"result":"failed","title":"Reactions With Partially Identical Annotations","summary":"Identify reactions in a pairwise manner that are annotated\nwith identical database references. This does not take into account a\nreaction's directionality or compartment.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\nIt could also be useful to identify a 'type' of reaction that\noccurs in several compartments.\n\nImplementation:\n\nIdentify duplicate reactions globally by checking if any\ntwo metabolic reactions have the same entries in their annotation\nattributes. The heuristic looks at annotations with the keys\n\"metanetx.reaction\", \"kegg.reaction\", \"brenda\", \"rhea\", \"biocyc\",\n\"bigg.reaction\" only.","message":"Based on annotations there are 32 different groups of overlapping\nannotation which corresponds to a total of 71 duplicated reactions in\nthe model.","data":{"biocyc:META:TRANS-RXN-233,metanetx.reaction:MNXR100259":["EX_gln__L_e","GLNtex"],"metanetx.reaction:MNXR100484,rhea:28695,rhea:28696,rhea:28697,rhea:28698":["HCO3tex","EX_hco3_e"],"biocyc:META:RXN0-16,biocyc:META:TRANS-RXN0-487,metanetx.reaction:MNXR101670,rhea:28699,rhea:28700,rhea:28701,rhea:28702":["MNtex","EX_mn2_e"],"biocyc:META:RXN66-448,metanetx.reaction:MNXR95951,rhea:32143,rhea:32144,rhea:32145,rhea:32146":["ARGtex","EX_arg__L_e"],"biocyc:META:TRANS-RXN-145,biocyc:META:TRANS-RXN0-547,metanetx.reaction:MNXR98641,rhea:29667,rhea:29668,rhea:29669,rhea:29670":["H2Otex","EX_h2o_e","H2Otu_syn","H2Otpp"],"biocyc:META:RXN-14452,metanetx.reaction:MNXR100765,rhea:34979,rhea:34980,rhea:34981,rhea:34982":["Htex","EX_h_e"],"biocyc:META:TRANS-RXN0-474,metanetx.reaction:MNXR102090":["O2tpp","O2tex","O2tu","EX_o2_e"],"biocyc:META:TRANS-RXN-141,metanetx.reaction:MNXR101507,rhea:29827,rhea:29828,rhea:29829,rhea:29830":["MG2tex","EX_mg2_e"],"metanetx.reaction:MNXR103339":["PTRCtex","EX_ptrc_e"],"biocyc:META:RXN-9615,biocyc:META:TRANS-RXN0-206,biocyc:META:TRANS-RXN0-544,metanetx.reaction:MNXR101950,rhea:28747,rhea:28748,rhea:28749,rhea:28750":["NH4tpp","NH4tex","EX_nh4_e"],"biocyc:META:TRANS-RXN-144,biocyc:META:TRANS-RXN0-497,metanetx.reaction:MNXR96436,rhea:29671,rhea:29672,rhea:29673,rhea:29674":["EX_ca2_e","CA2tex"],"biocyc:META:TRANS-RXN0-545,metanetx.reaction:MNXR96810":["CO2tex","EX_co2_e","CO2tpp"],"biocyc:META:TRANS-RXN-8,metanetx.reaction:MNXR99505,rhea:28486,rhea:28487,rhea:28488,rhea:28489":["EX_fe2_e","FE2tex"],"biocyc:META:RXN0-14,metanetx.reaction:MNXR96951,rhea:28703,rhea:28704,rhea:28705,rhea:28706":["EX_cu2_e","CU2tex"],"biocyc:META:TRANS-RXN-143,biocyc:META:TRANS-RXN-185,biocyc:META:TRANS-RXN-186,biocyc:META:TRANS-RXN-187,biocyc:META:TRANS-RXN-190,metanetx.reaction:MNXR100950,rhea:29463,rhea:29464,rhea:29465,rhea:29466":["EX_k_e","Ktex"],"biocyc:META:RXN66-447,metanetx.reaction:MNXR101057":["EX_leu__L_e","LEUtex"],"biocyc:META:TRANS-RXN-141A,metanetx.reaction:MNXR96821,rhea:28578,rhea:28579,rhea:28580,rhea:28581":["COBALT2tex","EX_cobalt2_e"],"metanetx.reaction:MNXR101992,rhea:34923,rhea:34924,rhea:34925,rhea:34926":["NO3tex","EX_no3_e"],"biocyc:META:RXN0-12,metanetx.reaction:MNXR105280,rhea:29351,rhea:29352,rhea:29353,rhea:29354":["EX_zn2_e","Zn2tex"],"metanetx.reaction:MNXR99522,rhea:34971,rhea:34972,rhea:34973,rhea:34974":["EX_fe3_e","FE3tex"],"metanetx.reaction:MNXR104469,rhea:34983,rhea:34984,rhea:34985,rhea:34986":["SO4tex","EX_so4_e"],"metanetx.reaction:MNXR104495,rhea:35039,rhea:35040,rhea:35041,rhea:35042":["SPMDtex","EX_spmd_e"],"metanetx.reaction:MNXR101690,rhea:34907,rhea:34908,rhea:34909,rhea:34910":["MOBDtex","EX_mobd_e"],"biocyc:META:TRANS-RXN-141B,metanetx.reaction:MNXR101958,rhea:29831,rhea:29832,rhea:29833,rhea:29834":["EX_ni2_e","NI2tex"],"biocyc:META:TRANS-RXN-189,metanetx.reaction:MNXR101804,rhea:34963,rhea:34964,rhea:34965,rhea:34966":["NAtex","EX_na1_e"],"biocyc:META:TRANS-RXN-14,metanetx.reaction:MNXR96963":["CYNTtex","EX_cynt_e"],"biocyc:META:TRANS-RXN0-459,metanetx.reaction:MNXR101464,rhea:34871,rhea:34872,rhea:34873,rhea:34874":["EX_meoh_e","MEOHtrpp","MEOHtex"],"biocyc:META:TRANS-RXN0-470,metanetx.reaction:MNXR102871,rhea:32823,rhea:32824,rhea:32825,rhea:32826":["PItex","EX_pi_e"],"metanetx.reaction:MNXR95546":["AGM4PA","AGM4PApp"],"biocyc:META:TRANS-RXN-139,metanetx.reaction:MNXR96797,rhea:29823,rhea:29824,rhea:29825,rhea:29826":["CLtex","EX_cl_e"],"bigg.reaction:NDH_1_4_um":["NDH_1_4_um_copy2","NDH_1_4_um_copy1"],"bigg.reaction:NDH_1_1_um":["NDH_1_1_um_copy1","NDH_1_1_um_copy2"]},"format_type":"percent","metric":0.06995073891625615},"test_find_duplicate_reactions":{"duration":0.002351383000018359,"result":"passed","title":"Duplicate Reactions","summary":"Identify reactions in a pairwise manner that use the same set\nof metabolites including potentially duplicate metabolites. Moreover, it\nwill take a reaction's directionality and compartment into account.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\n\nImplementation:\n\nCompare reactions in a pairwise manner.\nFor each reaction, the metabolite annotations are checked for a description\nof the structure (via InChI and InChIKey).If they exist, substrates and\nproducts as well as the stoichiometries of any reaction pair are compared.\nOnly reactions where the substrates, products, stoichiometry and\nreversibility are identical are considered to be duplicates.\nThis test will not be able to identify duplicate reactions if there are no\nstructure annotations. Further, it will report reactions with\ndiffering bounds as equal if they otherwise match the above conditions.","message":"Based on metabolites, directionality and compartment there are a\ntotal of 0 reactions in the model which have duplicates:","data":[],"format_type":"percent","metric":0.0},"test_find_reactions_with_identical_genes":{"duration":0.22432191399997237,"result":"failed","title":"Reactions With Identical Genes","summary":"Identify reactions in a pairwise manner that use identical\nsets of genes. It does *not* take into account a reaction's directionality,\ncompartment, metabolites or annotations.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\n\nImplementation:\n\nCompare reactions in a pairwise manner and group reactions whose genes\nare identical. Skip reactions with missing genes.","message":"Based only on equal genes there are 94 different groups of\nidentical reactions which corresponds to a total of 274\nduplicated reactions in the model.","data":{"SYNPCC7942_RS00470":["DTMPK","URIDK2r"],"SYNPCC7942_RS07445":["ACOATA","KAS15"],"SYNPCC7942_RS04785":["3HAD80","OPMEACPD","3HAD60","3HAD120","3HAD160","3HAD140","3HAD180","3HAD40_2","3HAD100","OGMEACPD"],"SYNPCC7942_RS08210":["RNDR1","RNDR3","RNDR4","RNDR2"],"SYNPCC7942_RS07765":["HISTDb","HISTDa"],"SYNPCC7942_RS02095,SYNPCC7942_RS10880":["TRPS2","TRPS3","TRPS1"],"SYNPCC7942_RS05290":["HSTPT","PHETA1"],"SYNPCC7942_RS12700":["PCHLDA650","LPOR","PCHLDA430"],"SYNPCC7942_RS02490":["ALDD2y","GCALDDy","GLYALDDy"],"SYNPCC7942_RS13015":["DESAT16a","DESAT18a"],"SYNPCC7942_RS05420":["TMPPP_1","THZT"],"SYNPCC7942_RS12670":["NDPK8","NDPK6","NDPK5","NDPK1","NDPK7","NDPK3","NDPK4","NDPK2"],"SYNPCC7942_RS04030":["MTHFC","MTHFD"],"SYNPCC7942_RS10460":["GCATENEC","LYCOPC"],"SYNPCC7942_RS02020":["AICART","IMPC"],"SYNPCC7942_RS12930":["EHGLAT","ASPTA","TYRTA"],"SYNPCC7942_RS01465":["G1PACT","UAGDP"],"SYNPCC7942_RS02730":["OPMEACPS","3OAS100","3OAS180","3OAS120","KAS14","OGMEACPS","3OAS80","3OAS160","3OAS60","3OAS140"],"SYNPCC7942_RS10975":["OHPBAT","SPTc","AGTi"],"SYNPCC7942_RS03505":["3OAR180","3OAR100","3OAR120","3OAR140","OPMEACPR","3OAR60","3OAR80","OGMEACPR","3OAR40_2","3OAR160"],"SYNPCC7942_RS01045":["NAMNPP","NMNS"],"SYNPCC7942_RS08000":["PPK2","PPK"],"SYNPCC7942_RS10060":["PHYTES","PHYTES2_1"],"SYNPCC7942_RS04180":["SPP","SPS"],"SYNPCC7942_RS05900":["PANTS","CYTK1"],"SYNPCC7942_RS02075,SYNPCC7942_RS02720,SYNPCC7942_RS03350,SYNPCC7942_RS04735,SYNPCC7942_RS05140,SYNPCC7942_RS06400,SYNPCC7942_RS06405,SYNPCC7942_RS06760,SYNPCC7942_RS09705,SYNPCC7942_RS10390,SYNPCC7942_RS10395,SYNPCC7942_RS11800,SYNPCC7942_RS11900,SYNPCC7942_RS11905,SYNPCC7942_RS12755":["PSIum","PSICSum"],"SYNPCC7942_RS03035":["PFK_3","PFK"],"SYNPCC7942_RS10440":["P5CR","HPROb"],"SYNPCC7942_RS00360":["IPDPS_syn","DMPPS_syn"],"SYNPCC7942_RS08945":["GLYDHDA","ALAD_L"],"SYNPCC7942_RS00640":["EAR160y","EAR180y","EAR100y","EAR60y","EPMEACPR","EGMEACPR","EAR80y","EAR140y","EAR120y","EAR40y"],"SYNPCC7942_RS06730,SYNPCC7942_RS06735,SYNPCC7942_RS06740,SYNPCC7942_RS13075,SYNPCC7942_RS13080,SYNPCC7942_RS13085":["ZNabcpp","MNabc_1"],"SYNPCC7942_RS03210":["DHAD2","DHAD1"],"SYNPCC7942_RS02040,SYNPCC7942_RS05145":["ANS","ANS2"],"SYNPCC7942_RS01605":["ADSL1r","ADSL2r"],"SYNPCC7942_RS00540,SYNPCC7942_RS01040":["NNATr","NMNAT"],"SYNPCC7942_RS10055":["PDS1_1","PHYPQOX","PDS2_1"],"SYNPCC7942_RS07915":["DPR","KARI_23dhmp_1","KARI_1","KARA1"],"SYNPCC7942_RS02735":["TKT1","TKT2"],"SYNPCC7942_RS01490":["PPNCL3","PPCDC","PPNCL2"],"SYNPCC7942_RS08975,SYNPCC7942_RS08980":["CYTBD4um","CYTBD4cm"],"SYNPCC7942_RS09420":["HPYRRy","TRSARyr"],"SYNPCC7942_RS04025":["DMATT","FRTT","GRTT"],"SYNPCC7942_RS07385":["FBA","FBA3"],"SYNPCC7942_RS11515":["SPMDabcpp","PTRCabcpp"],"SYNPCC7942_RS10465":["NTD7","NTD6"],"SYNPCC7942_RS10115":["PRAMPC","PRATPP"],"SYNPCC7942_RS09615":["ORNTAC","ACGS"],"SYNPCC7942_RS09540":["ASPOb","ASPO6","ASPO5"],"SYNPCC7942_RS01255,SYNPCC7942_RS01260,SYNPCC7942_RS01265,SYNPCC7942_RS01270":["ARGabcpp","GLNabcpp"],"SYNPCC7942_RS12395":["BCAROHX","BCAROHX2"],"SYNPCC7942_RS07325":["GTPCII","DB4PS"],"SYNPCC7942_RS09670":["MPOMC1_1","MPOMMM","MPOMOR_1"],"SYNPCC7942_RS09625,SYNPCC7942_RS12945":["CITCIa","IPPMIa","IPPMIb","CITCIb"],"SYNPCC7942_RS07690":["ERTHMMOR","IPMD"],"SYNPCC7942_RS08860":["UM3PL","UAMAS","UM4PL"],"SYNPCC7942_RS00515,SYNPCC7942_RS01005":["NDHPQRcm","NDHPQRum"],"SYNPCC7942_RS00880,SYNPCC7942_RS04960":["BPNT2","BPNT"],"SYNPCC7942_RS07730":["ZCAROTDH1","ZCARDS"],"SYNPCC7942_RS10545":["PKETF","PKETX"],"SYNPCC7942_RS08020,SYNPCC7942_RS11780":["NI2uabcpp","CUabcpp"],"SYNPCC7942_RS02505":["RBFK","AFAT"],"SYNPCC7942_RS03225":["SPMS","SPRMS"],"SYNPCC7942_RS11240":["DADK","ADK1"],"SYNPCC7942_RS10670,SYNPCC7942_RS10675,Synpcc7942_2107":["NO2tabcpp","CYNTtabcpp"],"SYNPCC7942_RS00705,SYNPCC7942_RS12365":["ACLSa","ACLSb","ACHBSb"],"SYNPCC7942_RS01250,SYNPCC7942_RS09840":["GAPD","E4PD"],"SYNPCC7942_RS07455":["AGPATACP_OLE_PALM","AGPAT160","AGPATACP_OLE_HDE","AGPAT161","AGPATACP_HDE_PALM"],"SYNPCC7942_RS07440,SYNPCC7942_RS10435":["G3PAT1819Z_1","G3PAT161","G3PAT160"],"SYNPCC7942_RS04440":["GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_HDE","GLUDGE_HDE_PALM"],"SYNPCC7942_RS05560":["GLUDGS_OLE_PALM","GLUDGS_HDE_HDE","GLUDGS_OLE_HDE","GLUDGS_HDE_PALM"],"SYNPCC7942_RS02045":["DAGK161","DAGK_HDE_PALM","DAGK160","DAGK_OLE_PALM","DAGK_OLE_HDE"],"SYNPCC7942_RS02945":["SQDGS_HDE_PALM","SQDGS_PALM_PALM"],"SYNPCC7942_RS05065":["DGDGS_OLE_PALM","DGDGS_OLE_HDE","DGDGS_HDE_HDE","DGDGS_HDE_PALM"],"SYNPCC7942_RS01760":["BTNPL2","BACCL"],"SYNPCC7942_RS07220":["LIPATPT_1","LIPAMPL_1"],"SYNPCC7942_RS03485":["CXANHX","ZXANHX"],"SYNPCC7942_RS08430,SYNPCC7942_RS11615":["ALCD19","ALCD1"],"SYNPCC7942_RS10140,SYNPCC7942_RS10355":["MPTG","MPTG2"],"SYNPCC7942_RS12230":["GLYCOX2","GLYCOX1"],"SYNPCC7942_RS05765,SYNPCC7942_RS06375":["OANTILpp","OANTIabcpp"],"SYNPCC7942_RS08520,SYNPCC7942_RS09815":["MDDCP3pp","MDDCP2pp","MDDCP4pp","MDDCP1pp","MDDCP5pp"],"SYNPCC7942_RS02000":["MLTGY4pp","MLTGY2pp","MLTGY1pp","MLTGY3pp"],"SYNPCC7942_RS11990":["AGM4PA","AM4PA","AM3PA"],"SYNPCC7942_RS10825":["AGM4PApp","AGM3PApp"],"SYNPCC7942_RS09960":["4PCP","AM4PCP","AGM4PCP","UM4PCP"],"SYNPCC7942_RS01800":["AGMH","AGM3PH","AGM4PH"],"SYNPCC7942_RS05285":["ILETA","VALTA","LEUTA"],"SYNPCC7942_RS02275,SYNPCC7942_RS04245,SYNPCC7942_RS04250,SYNPCC7942_RS05995,SYNPCC7942_RS06675,SYNPCC7942_RS11355":["4PEPTabcpp","DALAabcpp","ALAALAabcpp"],"SYNPCC7942_RS04020":["PAPA_OLE_PALM","PAPA161","PAPA_OLE_HDE","PAPA_HDE_PALM","PAPA160"],"SYNPCC7942_RS02455,SYNPCC7942_RS02950":["MCTP1Bpp","MCTP1App","MCTP2App"],"SYNPCC7942_RS00800,SYNPCC7942_RS05425":["THISAT","THII"],"SYNPCC7942_RS01140,SYNPCC7942_RS01145,SYNPCC7942_RS01500,SYNPCC7942_RS01750,SYNPCC7942_RS02165,SYNPCC7942_RS03355,SYNPCC7942_RS03360,SYNPCC7942_RS03570,SYNPCC7942_RS03575,SYNPCC7942_RS03585,SYNPCC7942_RS04600,SYNPCC7942_RS05330,SYNPCC7942_RS06020,SYNPCC7942_RS06025,SYNPCC7942_RS06030,SYNPCC7942_RS07110,SYNPCC7942_RS08350,SYNPCC7942_RS08550,SYNPCC7942_RS08555,SYNPCC7942_RS09545,SYNPCC7942_RS09955,SYNPCC7942_RS10225,SYNPCC7942_RS11400,SYNPCC7942_RS12590,SYNPCC7942_RS13675,SYNPCC7942_RS13745,SYNPCC7942_RS13795,Synpcc7942_2010":["PSIICSum","PSIIum"],"SYNPCC7942_RS00700,SYNPCC7942_RS01755,SYNPCC7942_RS09815":["MDDEP4pp","MDDEP1pp","MDDEP3pp","MDDEP2pp"]},"format_type":"percent","metric":0.26995073891625615},"test_find_medium_metabolites":{"duration":0.00909192400001757,"result":"failed","title":"Medium Components","summary":"This test checks all boundary reactions in the model that permit flux\ntowards creating a metabolite, and reports those metabolites. This test\ndoes not have any mandatory 'pass' criteria.\n\nImplementation:\nIdentify the metabolite IDs of each reaction in the method\ncobra.Model.medium. Model.medium returns exchange reactions whose bounds\npermit the uptake of metabolites.","message":null,"data":["hco3_e","mn2_e","mg2_e","ca2_e","nh4_e","cu2_e","k_e","h2o_e","o2_e","co2_e","leu__L_e","cobalt2_e","no3_e","zn2_e","fe3_e","so4_e","mobd_e","na1_e","h_e","photon410_e","photon430_e","photon450_e","photon470_e","photon490_e","photon510_e","photon530_e","photon550_e","photon570_e","photon590_e","photon610_e","photon630_e","photon650_e","photon670_e","photon690_e","pi_e","tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","his__L_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","no2_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e"],"format_type":"count","metric":1.0},"test_biomass_presence":{"duration":0.00021242699995127623,"result":"passed","title":"Biomass Reactions Identified","summary":"The biomass composition aka biomass formulation aka biomass reaction\nis a common pseudo-reaction accounting for biomass synthesis in\nconstraints-based modelling. It describes the stoichiometry of\nintracellular compounds that are required for cell growth. While this\nreaction may not be relevant to modeling the metabolism of higher\norganisms, it is essential for single-cell modeling.\n\nImplementation:\nIdentifies possible biomass reactions using two principal steps:\n    1. Return reactions that include the SBO annotation \"SBO:0000629\" for\n    biomass.\nIf no reactions can be identifies this way:\n    1. Look for the ``buzzwords`` \"biomass\", \"growth\" and \"bof\" in reaction\n    IDs.\n    2. Look for metabolite IDs or names that contain the ``buzzword``\n    \"biomass\" and obtain the set of reactions they are involved in.\n    3. Remove boundary reactions from this set.\n    4. Return the union of reactions that match the buzzwords and of the\n    reactions that metabolites are involved in that match the buzzword.\nThis test checks if at least one biomass reaction is present.","message":"In this model 9 the following biomass reactions were\nidentified: BIOMASS_CARB, BIOMASS_CELL_WALL, BIOMASS_COFACTORS,\nBIOMASS_DNA, BIOMASS_MEM_LIPIDS, ...","data":["BIOMASS_CARB","BIOMASS_CELL_WALL","BIOMASS_COFACTORS","BIOMASS_DNA","BIOMASS_MEM_LIPIDS","BIOMASS_PIGMENTS","BIOMASS_PROTEIN","BIOMASS_RNA","BIOMASS__1"],"format_type":"count","metric":0.0},"test_biomass_consistency":{"duration":{"BIOMASS_CARB":0.00023458900000150607,"BIOMASS_CELL_WALL":0.0002554170000053091,"BIOMASS_COFACTORS":0.00034818000000313987,"BIOMASS_DNA":0.0002635719999943831,"BIOMASS_MEM_LIPIDS":0.0002506390000007741,"BIOMASS_PIGMENTS":0.0002860639999653358,"BIOMASS_PROTEIN":0.00021187499999086867,"BIOMASS_RNA":0.00022524100000964609,"BIOMASS__1":0.00027077599997937796},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"failed"},"title":"Biomass Consistency","summary":"This test only yields sensible results if all biomass precursor\nmetabolites have chemical formulas assigned to them.\nThe molecular weight of the biomass reaction in metabolic models is\ndefined to be equal to 1 g/mmol. Conforming to this is essential in order\nto be able to reliably calculate growth yields, to cross-compare models,\nand to obtain valid predictions when simulating microbial consortia. A\ndeviation from 1 - 1E-03 to 1 + 1E-06 is accepted.\n\nImplementation:\nMultiplies the coefficient of each metabolite of the biomass reaction with\nits molecular weight calculated from the formula, then divides the overall\nsum of all the products by 1000.","message":{"BIOMASS_CARB":"One or more of the biomass components do not have a defined\nformula or contain unspecified chemical groups.","BIOMASS_CELL_WALL":"The component molar mass of the biomass reaction BIOMASS_CELL_WALL\nsums up to 0.57142989442176             which is outside of the 1e-03\nmargin from 1 mmol / g[CDW] / h.","BIOMASS_COFACTORS":"The component molar mass of the biomass reaction BIOMASS_COFACTORS\nsums up to 1.0009205772282002             which is outside of the\n1e-03 margin from 1 mmol / g[CDW] / h.","BIOMASS_DNA":"The component molar mass of the biomass reaction BIOMASS_DNA sums up\nto 1.00000345570174             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS_MEM_LIPIDS":"The component molar mass of the biomass reaction BIOMASS_MEM_LIPIDS\nsums up to 1.0000000000161593             which is outside of the\n1e-03 margin from 1 mmol / g[CDW] / h.","BIOMASS_PIGMENTS":"The component molar mass of the biomass reaction BIOMASS_PIGMENTS sums\nup to 1.000569280708             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS_PROTEIN":"One or more of the biomass components do not have a defined\nformula or contain unspecified chemical groups.","BIOMASS_RNA":"The component molar mass of the biomass reaction BIOMASS_RNA sums up\nto 0.9999955663688002             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS__1":"The component molar mass of the biomass reaction BIOMASS__1 sums up to\n4.547473508864641e-16             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h."},"data":{"BIOMASS_CARB":null,"BIOMASS_CELL_WALL":0.57142989442176,"BIOMASS_COFACTORS":1.0009205772282002,"BIOMASS_DNA":1.00000345570174,"BIOMASS_MEM_LIPIDS":1.0000000000161593,"BIOMASS_PIGMENTS":1.000569280708,"BIOMASS_PROTEIN":null,"BIOMASS_RNA":0.9999955663688002,"BIOMASS__1":4.547473508864641e-16},"format_type":"number","metric":{"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_RNA":0.0,"BIOMASS__1":1.0},"score":{"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_RNA":1.0,"BIOMASS__1":0.0}},"test_biomass_default_production":{"duration":{"BIOMASS_CARB":0.004581488999974681,"BIOMASS_CELL_WALL":0.0028243360000033135,"BIOMASS_COFACTORS":0.002823374000001877,"BIOMASS_DNA":0.0027922659999717325,"BIOMASS_MEM_LIPIDS":0.0027883189999897695,"BIOMASS_PIGMENTS":0.0027777290000017274,"BIOMASS_PROTEIN":0.0028077650000000176,"BIOMASS_RNA":0.002808837000031872,"BIOMASS__1":0.002825658000006115},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Biomass Production In Default Medium","summary":"Using flux balance analysis this test optimizes the model for growth in\nthe medium that is set by default. Any non-zero growth rate is accepted to\npass this test.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and the model's default constraints.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.005266338786562521","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.004285301264398366","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 6.414476106457932e-05","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.00039349307207683107","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.00857060252879673","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.0010618922630018588","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.027555295677489867","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.006123399039442193","BIOMASS__1":"Using the biomass reaction BIOMASS__1 this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.053903160558470005"},"data":{"BIOMASS_CARB":0.005266338786562521,"BIOMASS_CELL_WALL":0.004285301264398366,"BIOMASS_COFACTORS":6.414476106457932e-05,"BIOMASS_DNA":0.00039349307207683107,"BIOMASS_MEM_LIPIDS":0.00857060252879673,"BIOMASS_PIGMENTS":0.0010618922630018588,"BIOMASS_PROTEIN":0.027555295677489867,"BIOMASS_RNA":0.006123399039442193,"BIOMASS__1":0.053903160558470005},"format_type":"number","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_open_production":{"duration":{"BIOMASS_CARB":0.01969851699999481,"BIOMASS_CELL_WALL":0.006205371000021387,"BIOMASS_COFACTORS":0.00596639499997309,"BIOMASS_DNA":0.005878902000006292,"BIOMASS_MEM_LIPIDS":0.005899980999970467,"BIOMASS_PIGMENTS":0.006037387000048966,"BIOMASS_PROTEIN":0.006249754999998913,"BIOMASS_RNA":0.006358116999990671,"BIOMASS__1":0.006201773999976012},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Biomass Production In Complete Medium","summary":"Using flux balance analysis this test optimizes the model for growth using\na complete medium i.e. unconstrained boundary reactions. Any non-zero\ngrowth rate is accepted to pass this test.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and after removing any constraints from all boundary reactions.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n9.044461745820453","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n7.359618309034922","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n0.1101628400975043","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n0.675788851018302","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n14.7192366180699","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n1.8237041595973353","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n47.323734334322836","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n10.516385407627276","BIOMASS__1":"Using the biomass reaction BIOMASS__1 this is the growth rate that can\nbe         achieved when the model is simulated on a complete medium\ni.e.         with all the boundary reactions unconstrained:\n92.57381520798678"},"data":{"BIOMASS_CARB":9.044461745820453,"BIOMASS_CELL_WALL":7.359618309034922,"BIOMASS_COFACTORS":0.1101628400975043,"BIOMASS_DNA":0.675788851018302,"BIOMASS_MEM_LIPIDS":14.7192366180699,"BIOMASS_PIGMENTS":1.8237041595973353,"BIOMASS_PROTEIN":47.323734334322836,"BIOMASS_RNA":10.516385407627276,"BIOMASS__1":92.57381520798678},"format_type":"number","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_precursors_default_production":{"duration":{"BIOMASS_CARB":0.10454090300004282,"BIOMASS_CELL_WALL":0.11037442999997893,"BIOMASS_COFACTORS":0.4523412350000058,"BIOMASS_DNA":0.1476756989999899,"BIOMASS_MEM_LIPIDS":0.22727755599999,"BIOMASS_PIGMENTS":0.1689905850000173,"BIOMASS_PROTEIN":0.31978476999995564,"BIOMASS_RNA":0.1339146840000467,"BIOMASS__1":0.2006693710000036},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Blocked Biomass Precursors In Default Medium","summary":"Using flux balance analysis this test optimizes for the production of each\nmetabolite that is a substrate of the biomass reaction with the exception\nof atp and h2o. Optimizations are carried out using the default\nconditions. This is useful when reconstructing the precursor biosynthesis\npathways of a metabolic model. To pass this test, the model should be able\nto synthesis all the precursors.\n\nImplementation:\nFor each biomass precursor (except ATP and H2O) add a temporary demand\nreaction, then carry out FBA with this reaction as the objective. Collect\nall metabolites for which this optimization is equal to zero or\ninfeasible.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated on the         provided default medium a total of 20\nprecursors         (95.24% of all precursors except h2o and atp)\ncannot be produced: ['leutrna_c', 'glytrna_c', 'argtrna_c',\n'iletrna_c', 'asntrna_c', 'protrna_c', 'trptrna_c', 'glutrna_c',\n'asptrna_c', 'lystrna_c', 'alatrna_c', 'tyrtrna_c', 'glntrna_c',\n'histrna_c', 'mettrna_c', 'phetrna_c', 'valtrna_c', 'cystrna_c',\n'thrtrna_c', 'sertrna_c']","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []"},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":[],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":["leutrna_c","glytrna_c","argtrna_c","iletrna_c","asntrna_c","protrna_c","trptrna_c","glutrna_c","asptrna_c","lystrna_c","alatrna_c","tyrtrna_c","glntrna_c","histrna_c","mettrna_c","phetrna_c","valtrna_c","cystrna_c","thrtrna_c","sertrna_c"],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"count","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.9523809523809523,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.04761904761904767,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_precursors_open_production":{"duration":{"BIOMASS_CARB":0.0959643430000483,"BIOMASS_CELL_WALL":0.1125981339999953,"BIOMASS_COFACTORS":0.4057600319999892,"BIOMASS_DNA":0.14484227600001987,"BIOMASS_MEM_LIPIDS":0.20739499700005126,"BIOMASS_PIGMENTS":0.1808918730000073,"BIOMASS_PROTEIN":0.19353040499998997,"BIOMASS_RNA":0.1308055480000121,"BIOMASS__1":0.18703204400003415},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Blocked Biomass Precursors In Complete Medium","summary":"Using flux balance analysis this test optimizes for the production of each\nmetabolite that is a substrate of the biomass reaction with the exception\nof atp and h2o. Optimizations are carried out using a complete\nmedium i.e. unconstrained boundary reactions. This is useful when\nreconstructing the precursor biosynthesis pathways of a metabolic model.\nTo pass this test, the model should be able to synthesis all the\nprecursors.\n\nImplementation:\nFirst remove any constraints from all boundary reactions, then for each\nbiomass precursor (except ATP and H2O) add a temporary demand\nreaction, then carry out FBA with this reaction as the objective. Collect\nall metabolites for which this optimization is below or equal to zero or is\ninfeasible.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated in         complete medium a total of 20 precursors\n(95.24% of all precursors except h2o and atp) cannot be produced:\n['leutrna_c', 'glytrna_c', 'argtrna_c', 'iletrna_c', 'asntrna_c',\n'protrna_c', 'trptrna_c', 'glutrna_c', 'asptrna_c', 'lystrna_c',\n'alatrna_c', 'tyrtrna_c', 'glntrna_c', 'histrna_c', 'mettrna_c',\n'phetrna_c', 'valtrna_c', 'cystrna_c', 'thrtrna_c', 'sertrna_c']","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []"},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":[],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":["leutrna_c","glytrna_c","argtrna_c","iletrna_c","asntrna_c","protrna_c","trptrna_c","glutrna_c","asptrna_c","lystrna_c","alatrna_c","tyrtrna_c","glntrna_c","histrna_c","mettrna_c","phetrna_c","valtrna_c","cystrna_c","thrtrna_c","sertrna_c"],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"count","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.9523809523809523,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.04761904761904767,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_gam_in_biomass":{"duration":{"BIOMASS_CARB":0.09904700199996341,"BIOMASS_CELL_WALL":0.09869193200000836,"BIOMASS_COFACTORS":0.09966221400003406,"BIOMASS_DNA":0.10048871899999767,"BIOMASS_MEM_LIPIDS":0.10130641699998932,"BIOMASS_PIGMENTS":0.10375364800000852,"BIOMASS_PROTEIN":0.10499291400003585,"BIOMASS_RNA":0.10519078300001183,"BIOMASS__1":0.10309037900003659},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"failed","BIOMASS__1":"passed"},"title":"Growth-associated Maintenance in Biomass Reaction","summary":"The growth-associated maintenance (GAM) term accounts for the energy in\nthe form of ATP that is required to synthesize macromolecules such as\nProteins, DNA and RNA, and other processes during growth. A GAM term is\ntherefore a requirement for any well-defined biomass reaction. There are\ndifferent ways to implement this term depending on\nwhat kind of experimental data is available and the preferred\nway of implementing the biomass reaction:\n- Chemostat growth experiments yield a single GAM value representing the\n  required energy per gram of biomass (Figure 6 of [1]_). This can be\n  implemented in a lumped biomass reaction or in the final term of a split\n  biomass reaction.\n- Experimentally delineating or estimating the GAM requirements\n  for each macromolecule separately is possible, yet requires either\n  data from multi-omics experiments [2]_ or detailed resources [1]_ ,\n  respectively. Individual energy requirements can either be implemented\n  in a split biomass equation on the term for each macromolecule, or, on\n  the basis of the biomass composition, they can be summed into a single\n  GAM value for growth and treated as mentioned above.\n\nThis test is only able to detect if a lumped biomass reaction or the final\nterm of a split biomass reaction contains this term. Hence, it will\nonly detect the use of a single GAM value as opposed to individual energy\nrequirements of each macromolecule. Both approaches, however, have\nits merits.\n\nImplementation:\nDetermines the metabolite identifiers of ATP, ADP, H2O, HO4P and H+ based\non an internal mapping table. Checks if ATP and H2O are a subset of the\nreactants and ADP, HO4P and H+ a subset of the products of the biomass\nreaction.\n\nReferences:\n.. [1] Thiele, I., & Palsson, B. Ø. (2010, January). A protocol for\n       generating a high-quality genome-scale metabolic reconstruction.\n       Nature protocols. Nature Publishing Group.\n       http://doi.org/10.1038/nprot.2009.203\n.. [2] Hackett, S. R., Zanotelli, V. R. T., Xu, W., Goya, J., Park, J. O.,\n       Perlman, D. H., Gibney, P. A., Botstein, D., Storey, J. D.,\n       Rabinowitz, J. D.  (2010, January). Systems-level analysis of\n       mechanisms regulating yeast metabolic flux\n       Science\n       http://doi.org/10.1126/science.aaf2786","message":{"BIOMASS_CARB":"No, BIOMASS_CARB does not contain a term for growth-associated\nmaintenance.","BIOMASS_CELL_WALL":"No, BIOMASS_CELL_WALL does not contain a term for growth-associated\nmaintenance.","BIOMASS_COFACTORS":"No, BIOMASS_COFACTORS does not contain a term for growth-associated\nmaintenance.","BIOMASS_DNA":"No, BIOMASS_DNA does not contain a term for growth-associated\nmaintenance.","BIOMASS_MEM_LIPIDS":"No, BIOMASS_MEM_LIPIDS does not contain a term for growth-associated\nmaintenance.","BIOMASS_PIGMENTS":"No, BIOMASS_PIGMENTS does not contain a term for growth-associated\nmaintenance.","BIOMASS_PROTEIN":"Yes, BIOMASS_PROTEIN contains a term for growth-associated\nmaintenance.","BIOMASS_RNA":"No, BIOMASS_RNA does not contain a term for growth-associated\nmaintenance.","BIOMASS__1":"Yes, BIOMASS__1 contains a term for growth-associated maintenance."},"data":{"BIOMASS_CARB":false,"BIOMASS_CELL_WALL":false,"BIOMASS_COFACTORS":false,"BIOMASS_DNA":false,"BIOMASS_MEM_LIPIDS":false,"BIOMASS_PIGMENTS":false,"BIOMASS_PROTEIN":true,"BIOMASS_RNA":false,"BIOMASS__1":true},"format_type":"raw","metric":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":1.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":0.0,"BIOMASS__1":1.0}},"test_fast_growth_default":{"duration":{"BIOMASS_CARB":0.018485886999997092,"BIOMASS_CELL_WALL":0.0031659250000188877,"BIOMASS_COFACTORS":0.003209587000014835,"BIOMASS_DNA":0.0029760099999975864,"BIOMASS_MEM_LIPIDS":0.0029949150000447844,"BIOMASS_PIGMENTS":0.002978424999980689,"BIOMASS_PROTEIN":0.002982082000016817,"BIOMASS_RNA":0.0031146180000405366,"BIOMASS__1":0.0032104579999554517},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"failed","BIOMASS__1":"failed"},"title":"Unrealistic Growth Rate In Default Medium","summary":"The growth rate of a metabolic model should not be faster than that of the\nfastest growing organism. This is based on a doubling time of Vibrio\nnatriegens which was reported to be 14.8 minutes by: Henry H. Lee, Nili\nOstrov, Brandon G. Wong, Michaela A. Gold, Ahmad S. Khalil,\nGeorge M. Church\nin https://www.biorxiv.org/content/biorxiv/early/2016/06/12/058487.full.pdf\n\nThe calculation ln(2)/(14.8/60) ~ 2.81 yields the corresponding growth\nrate.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and a model's default constraints. Then check if the objective\nvalue is higher than 2.81.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms.","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms.","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms."},"data":{"BIOMASS_CARB":false,"BIOMASS_CELL_WALL":false,"BIOMASS_COFACTORS":false,"BIOMASS_DNA":false,"BIOMASS_MEM_LIPIDS":false,"BIOMASS_PIGMENTS":false,"BIOMASS_PROTEIN":false,"BIOMASS_RNA":false,"BIOMASS__1":false},"format_type":"raw","metric":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0},"score":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0}},"test_direct_metabolites_in_biomass":{"duration":{"BIOMASS_CARB":0.0942761719999794,"BIOMASS_CELL_WALL":0.09305411900004401,"BIOMASS_COFACTORS":0.09291404800001146,"BIOMASS_DNA":0.09287168899999187,"BIOMASS_MEM_LIPIDS":0.09418705600000976,"BIOMASS_PIGMENTS":0.0936171910000212,"BIOMASS_PROTEIN":0.0926293859999987,"BIOMASS_RNA":0.09243825900000502,"BIOMASS__1":0.0933906279999519},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Ratio of Direct Metabolites in Biomass Reaction","summary":"Some biomass precursors are taken from the media and directly consumed by\nthe biomass reaction. It might not be a problem for ions or\nmetabolites for which the organism in question is auxotrophic. However,\ntoo many of these metabolites may be artifacts of automated gap-filling\nprocedures. Many gap-filling algorithms attempt to minimise the number of\nadded reactions. This can lead to many biomass precursors being\n\"direct metabolites\".\n\nThis test reports the ratio of direct metabolites to the total amount of\nprecursors to a given biomass reaction. It specifically looks for\nmetabolites that are only in either exchange, transport or biomass\nreactions. Bear in mind that this may lead to false positives in heavily\ncompartimentalized models.\n\nTo pass this test, the ratio of direct metabolites should be less than 50%\nof all biomass precursors. This is an arbitrary threshold but it takes\ninto account that while certain ions do not serve a relevant metabolic\nfunction, it may still be important to include them in the biomass\nreaction to account for the impact of their uptake energy costs.\n\nThis threshold is subject to change in the future.\n\nImplementation:\nIdentify biomass precursors (excluding ATP and H+), identify cytosol\nand extracellular compartment from an internal mapping table. Then,\ndetermine which precursors is only involved in transport, boundary and\nbiomass reactions. Using FBA with the biomass function as the objective\nthen determine whether the metabolite is taken up only to be consumed by\nthe biomass reaction.","message":{"BIOMASS_CARB":"BIOMASS_CARB contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_CELL_WALL":"BIOMASS_CELL_WALL contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_COFACTORS":"BIOMASS_COFACTORS contains a total of 2 direct metabolites (7.69%).\nSpecifically these are: ['na1_c', 'k_c'].","BIOMASS_DNA":"BIOMASS_DNA contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_MEM_LIPIDS":"BIOMASS_MEM_LIPIDS contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_PIGMENTS":"BIOMASS_PIGMENTS contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_PROTEIN":"BIOMASS_PROTEIN contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_RNA":"BIOMASS_RNA contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS__1":"BIOMASS__1 contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: []."},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":["na1_c","k_c"],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":[],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"percent","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.07692307692307693,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":0.9230769230769231,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_essential_precursors_not_in_biomass":{"duration":{"BIOMASS_CARB":0.9049357760000021,"BIOMASS_CELL_WALL":0.8981613039999843,"BIOMASS_COFACTORS":0.7797817439999903,"BIOMASS_DNA":0.8940518099999508,"BIOMASS_MEM_LIPIDS":0.8725806389999775,"BIOMASS_PIGMENTS":0.89961230199998,"BIOMASS_PROTEIN":0.7786048899999969,"BIOMASS_RNA":0.8763085449999721,"BIOMASS__1":0.8851871030000211},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"failed","BIOMASS__1":"failed"},"title":"Number of Missing Essential Biomass Precursors","summary":"There are universal components of life that make up the biomass of all\nknown organisms. These include all proteinogenic amino acids, deoxy- and\nribonucleotides, water and a range of metabolic cofactors.\n\nThis test reports the amount of biomass precursors that have been reported\nto be essential constituents of the biomass equation. All of the following\nprecursors need to be included in the biomass reaction to pass the test:\n\nAminoacids:\ntrp__L, cys__L, his__L, tyr__L, met__L, phe__L, ser__L, pro__L, asp__L,\nthr__L, gln__L, glu__L, ile__L, arg__L, lys__L, val__L, leu__L, ala__L,\ngly, asn__L\nDNA: datp, dctp, dttp, dgtp\nRNA: atp, ctp, utp, gtp\nCofactors: nad, nadp, amet, fad, pydx5p, coa, thmpp, fmn and h2o\n\nThese metabolites were selected based on the results presented by\nDOI:10.1016/j.ymben.2016.12.002\n\nPlease note, that the authors also suggest to count C1 carriers\n(derivatives of tetrahydrofolate(B9) or tetrahydromethanopterin) as\nuniversal cofactors. We have omitted these from this check because there\nare many individual compounds that classify as C1 carriers, and it is not\nclear a priori which one should be preferred. In a future update, we may\nconsider identifying these using a chemical ontology.\n\nImplementation:\nDetermine whether the model employs a lumped or split biomass reaction.\nThen, using an internal mapping table, try to identify the above list of\nessential precursors in list of precursor metabolites of either type of\nbiomass reaction. List IDs in the models namespace if the metabolite\nexists, else use the MetaNetX namespace if the metabolite does not exist\nin the model. Identifies the cytosol from an internal mapping\ntable, and assumes that all precursors exist in that compartment.","message":{"BIOMASS_CARB":"BIOMASS_CARB lacks a total of 35 essential metabolites\n(1750.00% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_CELL_WALL":"BIOMASS_CELL_WALL lacks a total of 35 essential metabolites\n(1750.00% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_COFACTORS":"BIOMASS_COFACTORS lacks a total of 31 essential metabolites\n(119.23% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'atp_c', 'gtp_c', 'ctp_c', 'utp_c',\n'amet_c', 'fmn_c', 'h2o_c'].","BIOMASS_DNA":"BIOMASS_DNA lacks a total of 2 essential metabolites         (50.00%\nof all biomass precursors). Specifically         these are:\n['pydx5p_c', 'thmpp_c'].","BIOMASS_MEM_LIPIDS":"BIOMASS_MEM_LIPIDS lacks a total of 35 essential metabolites\n(318.18% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_PIGMENTS":"BIOMASS_PIGMENTS lacks a total of 34 essential metabolites\n(485.71% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_PROTEIN":"BIOMASS_PROTEIN lacks a total of 34 essential metabolites\n(161.90% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'ctp_c', 'utp_c', 'nad_c', 'nadp_c',\n'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_RNA":"BIOMASS_RNA lacks a total of 2 essential metabolites         (66.67%\nof all biomass precursors). Specifically         these are:\n['pydx5p_c', 'thmpp_c'].","BIOMASS__1":"BIOMASS__1 lacks a total of 22 essential metabolites         (275.00%\nof all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'amet_c',\n'fmn_c']."},"data":{"BIOMASS_CARB":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_CELL_WALL":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_COFACTORS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","atp_c","gtp_c","ctp_c","utp_c","amet_c","fmn_c","h2o_c"],"BIOMASS_DNA":["pydx5p_c","thmpp_c"],"BIOMASS_MEM_LIPIDS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_PIGMENTS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_PROTEIN":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_RNA":["pydx5p_c","thmpp_c"],"BIOMASS__1":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","amet_c","fmn_c"]},"format_type":"count","metric":{"BIOMASS_CARB":17.5,"BIOMASS_CELL_WALL":17.5,"BIOMASS_COFACTORS":1.1923076923076923,"BIOMASS_DNA":0.5,"BIOMASS_MEM_LIPIDS":3.1818181818181817,"BIOMASS_PIGMENTS":4.857142857142857,"BIOMASS_PROTEIN":1.619047619047619,"BIOMASS_RNA":0.6666666666666666,"BIOMASS__1":2.75},"score":{"BIOMASS_CARB":-16.5,"BIOMASS_CELL_WALL":-16.5,"BIOMASS_COFACTORS":-0.1923076923076923,"BIOMASS_DNA":0.5,"BIOMASS_MEM_LIPIDS":-2.1818181818181817,"BIOMASS_PIGMENTS":-3.8571428571428568,"BIOMASS_PROTEIN":-0.6190476190476191,"BIOMASS_RNA":0.33333333333333337,"BIOMASS__1":-1.75}},"test_stoichiometric_consistency":{"duration":1.0388909499999954,"result":"failed","title":"Stoichiometric Consistency","summary":"Stoichiometric inconsistency violates universal constraints:\n1. Molecular masses are always positive, and\n2. On each side of a reaction the mass is conserved.\nA single incorrectly defined reaction can lead to stoichiometric\ninconsistency in the model, and consequently to unconserved metabolites.\nSimilar to insufficient constraints, this may give rise to cycles which\neither produce mass from nothing or consume mass from the model.\n\nImplementation:\nThis test uses an implementation of the algorithm presented in\nsection 3.1 by Gevorgyan, A., M. G Poolman, and D. A Fell.\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425","message":"This model's stoichiometry inconsistent","data":false,"format_type":"percent","metric":1.0},"test_unconserved_metabolites":{"duration":2.7814139310000314,"result":"failed","title":"Unconserved Metabolites","summary":"The list of unconserved metabolites is computed using the algorithm described\nin section 3.2 of\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425.","message":"This model contains 34 unconserved metabolites: photon630_e, h2o_c,\nphoton650_e, photon670_e, photon690_e, ...","data":["photon630_e","h2o_c","photon650_e","photon670_e","photon690_e","h_c","h2o_p","pho_loss_c","h2o_e","o2_cx","o2_e","o2_p","o2_c","h_p","o2_u","h2o2_c","o2s_c","photon410_e","h2_c","photon430_e","photon450_e","photon470_e","h2o_u","photon490_e","photon510_e","h_u","photon530_e","photon550_e","h_e","photon570_e","photon590_e","h2o_cx","photon610_e","h_cx"],"format_type":"count","metric":34},"test_inconsistent_min_stoichiometry":{"duration":7.410806337999986,"result":"failed","title":"Minimal Inconsistent Net Stoichiometries","summary":"Only 10 unconserved metabolites are reported and considered to\navoid computing for too long.\n\nImplementation:\nAlgorithm described in section 3.3 of\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425.","message":null,"data":[["h2o_e"],["photon630_e"],["photon650_e"],["photon670_e"],["h2o_p"],["h2o_c"],["photon690_e"],["pho_loss_c"],["o2_cx"],["h_c"]],"format_type":"count","metric":10},"test_detect_energy_generating_cycles":{"duration":{"MNXM3":0.15926178000000846,"MNXM63":0.15956487700003663,"MNXM51":0.16390319200002068,"MNXM121":0.16372367700000723,"MNXM423":0.018123639999998886,"MNXM6":0.12238822000000482,"MNXM10":0.11815813599997682,"MNXM38":0.01807658199999196,"MNXM208":0.11816272499999059,"MNXM191":0.013857359000041924,"MNXM223":0.012590201999955752,"MNXM7517":0.012525962999973217,"MNXM12233":0.011266238000018802,"MNXM558":0.011913778999996794,"MNXM21":0.16918259600004149,"MNXM89557":0.1672303590000297},"result":{"MNXM3":"failed","MNXM63":"passed","MNXM51":"passed","MNXM121":"passed","MNXM423":"skipped","MNXM6":"passed","MNXM10":"passed","MNXM38":"skipped","MNXM208":"passed","MNXM191":"skipped","MNXM223":"skipped","MNXM7517":"skipped","MNXM12233":"skipped","MNXM558":"skipped","MNXM21":"passed","MNXM89557":"passed"},"title":"Erroneous Energy-generating Cycles","summary":"When a model is not sufficiently constrained to account for the\nthermodynamics of reactions, flux cycles may form which provide reduced\nmetabolites to the model without requiring nutrient uptake. These cycles\nare referred to as erroneous energy-generating cycles. Their effect on the\npredicted growth rate in FBA may account for an increase of up to 25%,\nwhich makes studies involving the growth rates predicted from such models\nunreliable.\n\nImplementation:\nThis test uses an implementation of the algorithm presented by:\nFritzemeier, C. J., Hartleb, D., Szappanos, B., Papp, B., & Lercher,\nM. J. (2017). Erroneous energy-generating cycles in published genome scale\nmetabolic networks: Identification and removal. PLoS Computational\nBiology, 13(4), 1–14. http://doi.org/10.1371/journal.pcbi.1005494\n\nFirst attempt to identify the main compartment (cytosol), then attempt to\nidentify each metabolite of the referenced list of energy couples via an\ninternal mapping table. Construct a dissipation reaction for each couple.\nCarry out FBA with each dissipation reaction as the objective and report\nthose reactions that non-zero carry flux.","message":{"MNXM3":"The model can produce 'MNXM3' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 545 reactions are involved in\nthose cycles: EX_hco3_e, ADPT, O2tcx, AOXPBDC, DNTPPA, ...","MNXM63":"The model can produce 'MNXM63' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM51":"The model can produce 'MNXM51' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM121":"The model can produce 'MNXM121' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM6":"The model can produce 'MNXM6' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM10":"The model can produce 'MNXM10' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM208":"The model can produce 'MNXM208' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM21":"The model can produce 'MNXM21' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM89557":"The model can produce 'MNXM89557' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:"},"data":{"MNXM3":["EX_hco3_e","ADPT","O2tcx","AOXPBDC","DNTPPA","BIOMASS_PIGMENTS","H2Otu_syn","DTMPK","BIOMASS__1","ORNTA","5DOAN","3HAD160","RNDR3","Htex","HISTDa","TRPS3","DMBZIDS2","HSTPT","ORNDC","U23GAAT2","HOXGfx","PGK","IMPD","LPOR","CHRPL","GCALDDy","MSBENZMT","DESAT18a","FUM","PHYFXOR","TMPPP_1","VPAMTr","RNDR1","GLYCL","ACONT","NDPK7","GTPCI","AIRC2","IGPS","MTAP","DHORD3um","MTHFC","HBZNPT","GCATENEC","HSDy","HISTDb","UPPDC1","GARFT","H4THDPR","UDPG4E","GLCS3","AICART","ASPTA","PRAGSr","SQD1","ACKr","UDCPDPS","GK1","SHKK","G1PACT","3HAD60","PGI","OHPBAT","PQH2tum","O2tu","O2tpp","H2Otex","EX_mg2_e","3HAD80","3OAR160","PPK","GALUi","PHYTES2_1","IGPDH","OMPDC","NADS2","GLUTRR","UAMAGS","ADCL","CYTK1","DAPDC","PSIum","THRS","NAMNPP","FOLD3","P5CR","ICHORS","3OAS140","PPK2","GLYDHDA","SBP","H4THDPS","EAR60y","UAPGR","DHAD1","SUCBZL","ADSL1r","NNATr","PERD","PPBNGS","ADOCBLS","LTHRK","APRAUR","O2tex","ALAALAr","ADCPS2","GF6PTA","DNMPPA","PGMT","G5SADs","LPADSS2","DPR","EAR120y","MAN1PT","TKT2","PSP_L","PPNCL2","CHORS","CS","PPCDC","ADMDC","PPPGO2_1","BIOMASS_DNA","DMATT","G3PD2","BIOMASS_CELL_WALL","PHYTES","RB15BPtcx","MOHMT","FBA","RZ5PP","ASAD","CYSS_2","LYCOPC","ACOTA","3HAD180","ALDD2y","3OAS80","PSCVT","CBPS","MEPCT","PDX5POi","DHAD2","DHFS","PGCD","NNDMBRT","PRATPP","SERAT","PRAIS","PRAMPC","ACBIPGT","SEPHCHCS","ORNTAC","SUCBZS","UHGADA2","DHNANT","GGDPR","ASP1DC","PPNDH","ASPK","DXPS","ME2","3PGtcx","PAPSR","SADT","BIOMASS_COFACTORS","DPCOAK","ARGSL","HSK","MTHFD","PMDPHT","3HAD140","DAPE","BCAROHX2","HPPK","PANTS","AHCi","ALAD_L","GTPCII","GLCBRAN3","DB4PS","DXPRIi","FBA3","RBFSa","GLUTRS","MPOMMM","METAT","EAR160y","DHORTS","PDX5PS2","KARI_23dhmp_1","GAPDi_nadp","AIRC3","UMPK","RBFSb_1","SUCDum","FBP","CITCIb","TMPK","AGPR","CDPMEK","DVOCHR_1","H2CO3_NAt_syn","HEMEOS","PMANM","RPE","MPOMT_1","UAMAS","CYOOum","METS_1","PRUK","FNOR_1","GART","DMTPHT","DDPA","ASPCT","HSERTA","CYRDAAT","MECDPDHf","Htcx","H2Otpp","HISTP","MTHFR3_1","3HAD40_2","BIOMASS_MEM_LIPIDS","HCO3tcx","IMPC","BIOMASS_PROTEIN","LDAPAT","3OAR40_2","RNDR2","GRTT","NPDPS","3OAS100","ADSL2r","MAN6PI","3OAS120","EAR180y","DHQTi","3OAS60","EAR40y","MG2uabcpp","KARA1","TKT1","IPDDI","PKETF","ENO","UAGCVT","PRASCSi","PRFGS","MG2tex","TRDR","GLUPRT","PSERT","GMPS2","RBFK","NTRIRfx","ACS","DHNCOAS","MCOATA","ARGSS","HMBS","PTPATi","PGLYCP","HTHRPDH","UAGAAT2","SHK3Dr","ORPT","PRPPS","CITMS","SPODM","PGAMT","NNDPR","ADSK","MECDPS","FCLT","SHCHCS3","ADCYRS","ATPPRT","DHQS","ANPRT","ADK1","PRAIi","RBPCcx","UPP3S","DHNPA_1","NADK","BIOMASS_RNA","NADTRHD","PGM","FE3abcpp","DM_dialurate_c","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","2PGLYCtcx","FRTT","3OAS180","EAR80y","SK_amylose_c","EAR140y","EX_k_e","DHPPDA","DHFR","BCAROHX","EX_h2o_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","EX_fe3_e","EX_so4_e","AFAT","G1SAT","UAAGDS","URIDK2r","CHPHYS","EX_na1_e","PHETA1","DMPPS_syn","ANS2","3OAS160","ACHBSb","ADSS","THRPDC","MPOMOR_1","SPMS","EX_h_e","BPNT","ICDHyr","TMDS3","MTRI","CTPS2","FE3tex","AHSERL2_1","PEPC","CHORM","MPML","Nat_Kpp","TPI","E4PD","CPPPGO","PRMICI","CAT","GLUR","OCBT","GLGC","PYK","ALAR","SULR_2","ADCS","UGMDDS","IG3PS","RPI","NAt3pp","GLYCLTDx","FMNRy_1","GHMT2r","PGPP_OLE_PALM","EX_photon410_e","DM_amob_c","ADNK1","OPMEACPD","OPMEACPR","AGPAT160","AGPATACP_HDE_PALM","LEUtex","BTS6","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","HCO3tex","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","GLUDGS_HDE_HDE","TYRTRS","SQDGS_PALM_PALM","SO4tex","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","DGDGS_HDE_HDE","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","NAtex","PROTRS","GLYTRS","CYSTRS","ARGTRS","Ktex","TRPTRS","HISTRS","PHETRS","ASNTRS","ASPTRS","DBTS","THRTRS","LEUTRS","ILETRS","LYSTRS","AOXSr2","AMAOTr","LIPOS2","ALATRS","TRNFE","VALTRS","BACCL","LIPOCT","ZXANHX","PHOA410um","PHOA430um","OGMEACPR","PLYCOI","ZCARDS","PHOA650um","PHOA670um","GMAND","GFUCS","ETCHLAS","ETBCARO","COLIPAabcex","AACPS6","ALDR18","ALDDC17","THZT","PHYPQOX","CXANHX","OGMEACPS","A5PISO","KDOPS","KDOPP","NO2tex","KDOCT2","EGMEACPR","DXYTST","UAG2E","OANTS","ACGAMT","Htabcpp","ETAPCPSII","DEXZEAX","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","UAGPT3","GLYCOX1","PAPPT3","OANTIabcpp","OANTILpp","UDCPDP","ETCPC","NO2tabcpp","FALGTHLs","MALCOAMT","MDRPD","PSIICRum","ENOPH","QULNS","ILETA","ARD","VALTA","NDPK3","NDPK1","NDPK8","UNK3","NDPK5","NDPK4","ZISO","NDPK2","3OAR180","3OAR140","PAPA160","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","ACGK","LEUabcpp","ACLSa","SULabcpp","PAPA_OLE_PALM","TYRTA","ACLSb","OPMEACPS","EAR100y","KAS15","FALDH2","KARI_1","3HAD120","OGMEACPD","ACCOAC","ASPO5","PTHPS","CITCIa","3HAD100","PNTK","3OAR120","3OAR60","3OAR100","3OAR80","ALCD1","NDH_1_1_um_copy1","PCHLDA430","SFGTHi","SPR","RNDR4","TRPS2","PSICSum","PPND","CBFCum","THBTGT","THISAT","PSIIum","ATPSum","CYSDES","GLNS","THII","SHS1","PSIICSum","ASNS1","EX_no2_e","MDH","DRBK","DRPA","FA180ACPHi"],"MNXM63":[],"MNXM51":[],"MNXM121":[],"MNXM6":[],"MNXM10":[],"MNXM208":[],"MNXM21":[],"MNXM89557":[]},"format_type":"count","metric":{"MNXM3":0.5364173228346457,"MNXM63":0.0,"MNXM51":0.0,"MNXM121":0.0,"MNXM6":0.0,"MNXM10":0.0,"MNXM208":0.0,"MNXM21":0.0,"MNXM89557":0.0},"score":{"MNXM3":0.4635826771653543,"MNXM63":1.0,"MNXM51":1.0,"MNXM121":1.0,"MNXM6":1.0,"MNXM10":1.0,"MNXM208":1.0,"MNXM21":1.0,"MNXM89557":1.0}},"test_reaction_charge_balance":{"duration":0.0024554280000188555,"result":"failed","title":"Charge Balance","summary":"This will exclude biomass, exchange and demand reactions as they are\nunbalanced by definition. It will also fail all reactions where at\nleast one metabolite does not have a charge defined.\n\nIn steady state, for each metabolite the sum of influx equals the sum\nof efflux. Hence the net charges of both sides of any model reaction have\nto be equal. Reactions where at least one metabolite does not have a\ncharge are not considered to be balanced, even though the remaining\nmetabolites participating in the reaction might be.\n\nImplementation:\nFor each reaction that isn't a boundary or biomass reaction check if each\nmetabolite has a non-zero charge attribute and if so calculate if the\noverall sum of charges of reactants and products is equal to zero.","message":"A total of 40 (4.83%) reactions are charge unbalanced with at\nleast one of the metabolites not having a charge or the overall\ncharge not equal to 0: DRBK, MPTS, PSIum, PSIIum, DPGM, ...","data":["DRBK","MPTS","PSIum","PSIIum","DPGM","RBPCcx","CPMPS","GTPC","FNOR","PC6YM","MOGDS","DRPA","GUACYC","RDXRr","FA100ACPHi","OANTS","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","ICLIPAS","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","CYOOum"],"format_type":"count","metric":0.04825090470446321},"test_reaction_mass_balance":{"duration":0.031044521000012537,"result":"failed","title":"Mass Balance","summary":"This will exclude biomass, exchange and demand reactions as they are\nunbalanced by definition. It will also fail all reactions where at\nleast one metabolite does not have a formula defined.\n\nIn steady state, for each metabolite the sum of influx equals the sum\nof efflux. Hence the net masses of both sides of any model reaction have\nto be equal. Reactions where at least one metabolite does not have a\nformula are not considered to be balanced, even though the remaining\nmetabolites participating in the reaction might be.\n\nImplementation:\nFor each reaction that isn't a boundary or biomass reaction check if each\nmetabolite has a non-zero elements attribute and if so calculate if the\noverall element balance of reactants and products is equal to zero.","message":"A total of 38 (4.58%) reactions are mass unbalanced with at least\none of the metabolites not having a formula or the overall mass not\nequal to 0: MOCOS, MPTS, PCHLDA650, PSIIum, PCHLDA430, ...","data":["MOCOS","MPTS","PCHLDA650","PSIIum","PCHLDA430","SUCRt2","MOADSUx","RBPCcx","PHOA410um","MPTAT","MPTSS","PHOA430um","CPMPS","PHOA490um","GTPC","PHOA510um","FNOR","PC6YM","PHOA450um","MOGDS","PHOA470um","STACPSI","ETAPCPSII","OANTS","STCHLPSIum","COLIPAabcex","FA180ACPHi","FA181ACPHi","PHOA690um","ICLIPAabcpp","ETBCARO","ICLIPAS","ETCHLAS","FACOAE181","FACOAL181i","CYOOum","OANTIabcpp","OANTILpp"],"format_type":"count","metric":0.045838359469240045},"test_blocked_reactions":{"duration":1.2518409740000038,"result":"failed","title":"Universally Blocked Reactions","summary":"Universally blocked reactions are reactions that during Flux Variability\nAnalysis cannot carry any flux while all model boundaries are open.\nGenerally blocked reactions are caused by network gaps, which can be\nattributed to scope or knowledge gaps.\n\nImplementation:\nUse flux variability analysis (FVA) implemented in\ncobra.flux_analysis.find_blocked_reactions with open_exchanges=True.\nPlease refer to the cobrapy documentation for more information:\nhttps://cobrapy.readthedocs.io/en/stable/autoapi/cobra/flux_analysis/\nvariability/index.html#cobra.flux_analysis.variability.\nfind_blocked_reactions","message":"There are 229 (22.56%) blocked reactions in         the model:\nEX_mn2_e, HEMEAS_1, GLYOX, NMNS, G1PTT, ...","data":["EX_mn2_e","HEMEAS_1","GLYOX","NMNS","G1PTT","ZNabcpp","DNAMTn2r","MI3PP","PROAKGOX1","NTD6","G1PCTYT","DDPGA","DPOR","ARGOXRum","MNabc_1","CPPPGO2","EX_ca2_e","GLYALDDy","HPROb","NI2uabcpp","TDPDRR","TDPGDH","TDPDRE","SPRMS","CUabcpp","TRSARyr","MOBDabcpp","EX_fe2_e","PQH2tcm","EX_cu2_e","SK_14glucan_c","SK_glycogen_c","EX_zn2_e","EX_mobd_e","DADK","EX_ni2_e","ARGDHpp","GLYOX_1","FE2tex","NI2tex","MNtex","CU2tex","H2Otcx","Zn2tex","QUERT","MOBDtex","CA2tex","UDPGLDC","CHLADMT_1","FMETTRS","BTNPL2","LIPAMPL_1","LIPATPT_1","CPH4S","CDGS","CCGS","CDGR","SAMTRI","EPXQR","UPPRT","UDPGD","MLDCP1App","CDPGLC46DH","ALCD19","MLDCP1Bpp","MLDCP2App","MLDCP2Bpp","PFOR","MLTGY2pp","MLTGY3pp","CLtex","EX_cl_e","AGM3PApp","CELLSYN","ALAALAabcpp","PHEOASE","MCTP1Bpp","PHEOX_1","EHGLAT","PHYTK","NDH_1_4_um_copy2","AMANAPEr","CLt3_1pp","Ktu","NDH_1_1_um_copy2","MDDCP5pp","MDDEP2pp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX_glyc_e","EX_fuc__L_e","EX_glcur_e","EX_glcn_e","EX_glyc3p_e","EX_xyl__D_e","EX_lac__L_e","EX_g6p_e","EX_malt_e","EX_melib_e","EX_thymd_e","EX_galctn__D_e","EX_rib__D_e","EX_rmn_e","EX_fru_e","EX_ac_e","EX_glc__D_e","EX_asn__L_e","EX_uri_e","EX_12ppd__S_e","EX_akg_e","EX_lcts_e","EX_malttr_e","EX_dad_2_e","EX_adn_e","EX_g1p_e","EX_f6p_e","EX_ins_e","EX_cit_e","EX_inost_e","EX_fum_e","EX_ppa_e","EX_galct__D_e","EX_glyclt_e","EX_mal__D_e","EX_mal__L_e","EX_ser__L_e","EX_thr__L_e","EX_ala__L_e","EX_acac_e","EX_acmana_e","EX_galur_e","EX_peamn_e","EX_etha_e","EX_tym_e","EX_lyx__L_e","EX_pyr_e","EX_galctn__L_e","EX_acnam_e","EX_all__D_e","EX_4abut_e","EX_but_e","EX_dca_e","EX_5dglcn_e","EX_hxa_e","EX_tartr__L_e","EX_lys__L_e","EX_met__L_e","EX_gly_e","EX_his__L_e","EX_hom__L_e","EX_ile__L_e","EX_orn_e","EX_phe__L_e","EX_val__L_e","EX_dha_e","EX_cys__L_e","EX_urea_e","EX_trp__L_e","EX_tyr__L_e","EX_agm_e","EX_acgal_e","EX_gam_e","EX_ura_e","EX_ade_e","EX_cytd_e","EX_csn_e","EX_gua_e","EX_gsn_e","EX_thym_e","EX_xan_e","EX_xtsn_e","EX_alltn_e","EX_23camp_e","EX_3amp_e","EX_gmp_e","EX_23cgmp_e","EX_3gmp_e","EX_cmp_e","EX_23ccmp_e","EX_gam6p_e","EX_3cmp_e","EX_ump_e","EX_23cump_e","EX_man6p_e","EX_pser__L_e","EX_thrp_e","EX_3ump_e","EX_tyrp_e","EX_minohp_e","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","FNOR","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA181ACPHi","FA80ACPHi","GLCP4","GLCP3"],"format_type":"count","metric":0.22561576354679802},"test_find_stoichiometrically_balanced_cycles":{"duration":2.480628825999986,"result":"failed","title":"Stoichiometrically Balanced Cycles","summary":"Stoichiometrically Balanced Cycles are artifacts of insufficiently\nconstrained networks resulting in reactions that can carry flux when\nall the boundaries have been closed.\n\nImplementation:\nClose all model boundary reactions and then use flux variability analysis\n(FVA) to identify reactions that carry flux.","message":"There are 10 (0.99%) reactions         which participate in SBC in the\nmodel: GLCS3, PPK, GLYDHDA, GLCP2_1, ALAD_L, ...","data":["GLCS3","PPK","GLYDHDA","GLCP2_1","ALAD_L","GAPDi_nadp","NADTRHD","GAPD","GLGC","AGTi"],"format_type":"count","metric":0.009852216748768473},"test_find_orphans":{"duration":0.009595750000016778,"result":"failed","title":"Orphan Metabolites","summary":"Orphans are metabolites that are only consumed but not produced by\nreactions in the model. They may indicate the presence of network and\nknowledge gaps.\n\nImplementation:\nFind orphan metabolites structurally by considering only reaction\nequations and bounds. FBA is not carried out.","message":"A total of 13 (1.41%) metabolites are not produced by any reaction\nof the model: 2h3oppan_c, mi3p__D_c, 1p3h5c_c, dna_c, accp_c, ...","data":["2h3oppan_c","mi3p__D_c","1p3h5c_c","dna_c","accp_c","lipoate_c","fldox_c","cl_c","acmama_c","csn_c","cyst-L_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.01406926406926407},"test_find_deadends":{"duration":0.007928395000021737,"result":"failed","title":"Dead-end Metabolites","summary":"Dead-ends are metabolites that can only be produced but not consumed by\nreactions in the model. They may indicate the presence of network and\nknowledge gaps.\n\nImplementation:\nFind dead-end metabolites structurally by considering only reaction\nequations and bounds. FBA is not carried out.","message":"A total of 27 (2.92%) metabolites are not consumed by any reaction\nof the model: mn2_c, sprm_c, 5g2oxpt_c, inost_c, ni2_c, ...","data":["mn2_c","sprm_c","5g2oxpt_c","inost_c","ni2_c","dtdprmn_c","4hpro_LT_c","cdp4dh6doglc_c","dna5mtc_c","rcc_c","btnCCP_c","murein5px3p_p","quetrna_c","udpxyl_c","LalaDgluMdap_p","fldrd_c","5g2oxpt_p","fmettrna_c","h2o2_p","b14glucan_c","iscs_c","38ch2gtp_c","fdxo_2_2_c","mocogdp_c","acmam_c","g15lac_c","35cgmp_c"],"format_type":"count","metric":0.02922077922077922},"test_find_disconnected":{"duration":0.0005281070000364707,"result":"passed","title":"Metabolite Connectivity","summary":"Disconnected metabolites are not part of any reaction in the model. They\nare most likely left-over from the reconstruction process, but may also\npoint to network and knowledge gaps.\n\nImplementation:\nCheck for any metabolites of the cobra.Model object with emtpy reaction\nattribute.","message":"A total of 0 (0.00%) metabolites are not associated with any\nreaction of the model:","data":[],"format_type":"count","metric":0.0},"test_find_metabolites_not_produced_with_open_bounds":{"duration":82.91112053699999,"result":"failed","title":"Metabolite Production In Complete Medium","summary":"In complete medium, a model should be able to divert flux to every\nmetabolite. This test opens all the boundary reactions i.e. simulates a\ncomplete medium and checks if any metabolite cannot be produced\nindividually using flux balance analysis. Metabolites that cannot be\nproduced this way are likely orphan metabolites, downstream of reactions\nwith fixed constraints, or blocked by a cofactor imbalance. To pass this\ntest all metabolites should be producible.\n\nImplementation:\nOpen all model boundary reactions, then for each metabolite in the model\nadd a boundary reaction and maximize it with FBA.","message":"A total of 147 (15.91%) metabolites cannot be produced in complete\nmedium: 1p3h5c_c, 2h3oppan_c, 3hbutACP_c, 3hddecACP_c, 3hdecACP_c, ...","data":["1p3h5c_c","2h3oppan_c","3hbutACP_c","3hddecACP_c","3hdecACP_c","3hhexACP_c","3hmrsACP_c","3hoctACP_c","3hoctaACP_c","3hpalmACP_c","3oddecACP_c","3odecACP_c","3ohexACP_c","3omrsACP_c","3ooctACP_c","3ooctdACP_c","3opalmACP_c","4h2oglt_c","5g2oxpt_p","ACP_c","acACP_c","accp_c","acmam_c","acmama_c","actACP_c","alaala_p","alatrna_c","allocy_c","allocy_exc_c","argtrna_c","asntrna_c","asptrna_c","athis_c","bglyg4n_c","btnCCP_c","but2eACP_c","butACP_c","cl_c","csn_c","cyst-L_c","cystrna_c","dcaACP_c","ddcaACP_c","dna5mtc_c","dna_c","e4hglu_c","egmeACP_c","epmeACP_c","fdxo_2_2_c","fdxox_c","fdxrd_c","fldox_c","fldrd_c","fmettrna_c","gcaro_c","glntrna_c","glutrna_c","glyg4n_c","glytrna_c","gmeACP_c","h2o2_p","hdeACP_c","hexACP_c","hgmeACP_c","histrna_c","hpmeACP_c","iletrna_c","inost_c","iscs_c","iscsh_c","iscssh_c","leutrna_c","lgt__S_c","lipamp_c","lipoate_c","lyc_c","lystrna_c","malACP_c","mettrna_c","mi3p__D_c","moadamp_c","moadcoo_c","moadcosh_c","moco_c","mocogdp_c","mpt_c","mptamp_c","mthgxl_c","myrsACP_c","ocACP_c","ocdcaACP_c","octe9ACP_c","ogmeACP_c","opmeACP_c","p680_exc_um","p680_um","p700_exc_um","p700_um","palmACP_c","pcox_u","pcrd_u","phetrna_c","phytol_c","pimACP_c","pmeACP_c","protrna_c","ps2d1_exc_um","ps2d1_um","rdxo_c","rdxr_c","sertrna_c","tddec2eACP_c","tdec2eACP_c","thex2eACP_c","this_c","thissh_c","thrtrna_c","tmrs2eACP_c","toct2eACP_c","toctd2eACP_c","tpalm2eACP_c","trdox_c","trdrd_c","trnaala_c","trnaarg_c","trnaasn_c","trnaasp_c","trnacys_c","trnagln_c","trnaglu_c","trnagly_c","trnahis_c","trnaile_c","trnaleu_c","trnalys_c","trnamet_c","trnaphe_c","trnapro_c","trnaser_c","trnathr_c","trnatrp_c","trnatyr_c","trnaval_c","trptrna_c","tyrtrna_c","ura_c","valtrna_c"],"format_type":"count","metric":0.1590909090909091},"test_find_metabolites_not_consumed_with_open_bounds":{"duration":23.15690213099998,"result":"failed","title":"Metabolite Consumption In Complete Medium","summary":"In complete medium, a model should be able to divert flux from every\nmetabolite. This test opens all the boundary reactions i.e. simulates a\ncomplete medium and checks if any metabolite cannot be consumed\nindividually using flux balance analysis. Metabolites that cannot be\nconsumed this way are likely dead-end metabolites or upstream of reactions\nwith fixed constraints. To pass this test all metabolites should be\nconsumable.\n\nImplementation:\nOpen all model boundary reactions, then for each metabolite in the model\nadd a boundary reaction and minimize it with FBA.","message":"A total of 186 (20.13%) metabolites cannot be consumed in complete\nmedium: 1p3h5c_c, 35cgmp_c, 38ch2gtp_c, 3hbutACP_c, 3hddecACP_c, ...","data":["1p3h5c_c","35cgmp_c","38ch2gtp_c","3hbutACP_c","3hddecACP_c","3hdecACP_c","3hhexACP_c","3hmrsACP_c","3hoctACP_c","3hoctaACP_c","3hpalmACP_c","3oddecACP_c","3odecACP_c","3ohexACP_c","3omrsACP_c","3ooctACP_c","3ooctdACP_c","3opalmACP_c","4hpro_LT_c","5g2oxpt_c","5g2oxpt_p","ACP_c","LalaDgluMdap_p","acACP_c","accp_c","acmam_c","acmama_c","actACP_c","alatrna_c","allocy_c","allocy_exc_c","anhgm3p_p","argtrna_c","asntrna_c","asptrna_c","athis_c","b14glucan_c","btnCCP_c","but2eACP_c","butACP_c","cdg_c","cdp4dh6doglc_c","cdpglc_c","cph4_c","cpmp_c","cu2_c","cystrna_c","dcaACP_c","dca_c","dcacoa_c","ddcaACP_c","ddca_c","ddcacoa_c","dna5mtc_c","dna_c","dtdp4d6dg_c","dtdp4d6dm_c","dtdpglu_c","dtdprmn_c","egmeACP_c","epmeACP_c","epxqtrna_c","fdxo_2_2_c","fdxox_c","fdxrd_c","fldox_c","fldrd_c","fmettrna_c","g15lac_c","gcaro_c","glntrna_c","glutrna_c","glytrna_c","gmeACP_c","h2o2_p","hdca_c","hdcea_c","hdcoa_c","hdeACP_c","hexACP_c","hgmeACP_c","histrna_c","hpmeACP_c","iletrna_c","imgly_c","inost_c","iscs_c","iscsh_c","iscssh_c","leutrna_c","lyc_c","lystrna_c","malACP_c","mettrna_c","mi3p__D_c","mn2_c","moadamp_c","moadcoo_c","moadcosh_c","mobd_c","moco_c","mocogdp_c","mpt_c","mptamp_c","murein3p3p_p","murein3px4p_p","murein4p3p_p","murein5p3p_p","murein5px3p_p","myrsACP_c","ni2_c","ocACP_c","occoa_c","ocdcaACP_c","octa_c","octe9ACP_c","octe9_c","octe9coa_c","ogmeACP_c","opmeACP_c","p680_exc_um","p680_um","p700_exc_um","p700_um","palmACP_c","pcox_u","pcrd_u","phetrna_c","phphbda_c","phptna_c","pimACP_c","pmeACP_c","pmtcoa_c","pq_cm","pqh2_cm","preq0_c","preq1_c","preqtrna_c","protrna_c","ps2d1_exc_um","ps2d1_um","quetrna_c","rcc_c","rdxo_c","rdxr_c","sertrna_c","sprm_c","tdcoa_c","tddec2eACP_c","tdec2eACP_c","thex2eACP_c","this_c","thissh_c","thrtrna_c","tmrs2eACP_c","toct2eACP_c","toctd2eACP_c","tpalm2eACP_c","trdox_c","trdrd_c","trnaala_c","trnaarg_c","trnaasn_c","trnaasp_c","trnacys_c","trnagln_c","trnaglu_c","trnagly_c","trnahis_c","trnaile_c","trnaleu_c","trnalys_c","trnamet_c","trnaphe_c","trnapro_c","trnaser_c","trnathr_c","trnatrp_c","trnatyr_c","trnaval_c","trptrna_c","ttdca_c","tyrtrna_c","udpglcur_c","udpxyl_c","valtrna_c"],"format_type":"count","metric":0.2012987012987013},"test_find_reactions_unbounded_flux_default_condition":{"duration":2.276978875999987,"result":"failed","title":"Unbounded Flux In Default Medium","summary":"A large fraction of model reactions able to carry unlimited flux under\ndefault conditions indicates problems with reaction directionality,\nmissing cofactors, incorrectly defined transport reactions and more.\n\nImplementation:\nWithout changing the default constraints run flux variability analysis.\nFrom the FVA results identify those reactions that carry flux equal to the\nmodel's maximal or minimal flux.","message":" A fraction of 12.06% of the non-blocked reactions (in total 92\nreactions) can carry unbounded flux in the default model\ncondition. Unbounded reactions may be involved in\nthermodynamically infeasible cycles: ATPM, PGK, VPAMTr, GLCS3, PPK,\n...","data":["ATPM","PGK","VPAMTr","GLCS3","PPK","PSIum","PFK_3","GLYDHDA","SBP","ALAALAr","PGMT","GLYCK","PSP_L","HPYRRy","FBA","PGCD","CA2abcpp","3PGtcx","ALAD_L","FBA3","GAPDi_nadp","NTD7","FBP","BPNT2","PSERT","SPTc","ADSK","PPA","ADK1","NADTRHD","PFK","GLGC","PYK","CA2t2pp","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","ADNK1","EX_photon530_e","EX_photon550_e","EX_photon570_e","EX_photon590_e","EX_photon610_e","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","DAGK160","DAGK_HDE_PALM","DAGK161","AGTi","PHOA410um","PHOA430um","PHOA450um","PHOA470um","PHOA490um","PHOA510um","PHOA530um","PHOA550um","PHOA570um","PHOA590um","PHOA610um","PHOA630um","PHOA650um","PHOA670um","PHOA690um","DM_pho_loss_c","ETCHLAS","ETBCARO","Htabcpp","ETAPCPSII","STACPSI","ETCPC","PSICRum","NDPK1","ALAALAD","NDPK2","PAPA160","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","PAPA_OLE_PALM","DAGK_OLE_HDE","DAGK_OLE_PALM","PSICSum","CBFCum","PCXHtpp","GLNS","PSIICSum"],"format_type":"percent","metric":0.12057667103538663},"test_gene_essentiality_from_data_qualitative":{"duration":{"knockouts":3.0067354079999973},"result":{"knockouts":"failed"},"title":"Gene Essentiality Prediction","summary":"The in-silico gene essentiality is compared with experimental\ndata and the accuracy is expected to be better than 0.95.\nIn principal, Matthews' correlation coefficient is a more comprehensive\nmetric but is a little fragile to not having any false negatives or false\npositives in the output.\n\nImplementation:\nRead and validate experimental config file and data tables. Constrain the\nmodel with the parameters provided by a user's definition of the medium,\nthen compute a confusion matrix based on the predicted essential, expected\nessential, predicted nonessential and expected nonessential genes.\nThe individual values of the confusion matrix are calculated as described\nin https://en.wikipedia.org/wiki/Confusion_matrix","message":{"knockouts":"Ideally, every model would show a perfect accuracy of 1. In\nname 'knockouts' the model has  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Prediction","summary":"The in-silico growth prediction is compared with experimental\ndata and the accuracy is expected to be better than 0.95.\nIn principal, Matthews' correlation coefficient is a more comprehensive\nmetric but is a little fragile to not having any false negatives or false\npositives in the output.\n\nImplementation:\nRead and validate experimental config file and data tables. Constrain the\nmodel with the parameters provided by a user's definition of the medium,\nthen compute a confusion matrix based on the predicted true, expected\ntrue, predicted false and expected false growth.\nThe individual values of the confusion matrix are calculated as described\nin https://en.wikipedia.org/wiki/Confusion_matrix","message":{},"data":{},"format_type":"percent","metric":{},"score":{}},"test_absolute_extreme_coefficient_ratio":{"duration":0.00810804999997572,"result":"passed","title":"Ratio Min/Max Non-Zero Coefficients","summary":"This test will return the absolute largest and smallest, non-zero\ncoefficients of the stoichiometric matrix. A large ratio of these values\nmay point to potential numerical issues when trying to solve different\nmathematical optimization problems such as flux-balance analysis.\n\nTo pass this test the ratio should not exceed 10^9. This threshold has\nbeen selected based on experience, and is likely to be adapted when more\ndata on solver performance becomes available.\n\nImplementation:\nCompose the stoichiometric matrix, then calculate absolute coefficients and\nlastly use the maximal value and minimal non-zero value to calculate the\nratio.","message":"The ratio of the absolute values of the largest coefficient 1080.0 and\nthe lowest, non-zero coefficient 0.0001 is: 1.08E+07.","data":10800000.0,"format_type":"percent","metric":0.0},"test_number_independent_conservation_relations":{"duration":0.23777489500002957,"result":"passed","title":"Independent Conservation Relations","summary":"This test will return the number of conservation relations, i.e.,\nconservation pools through the left null space of the stoichiometric\nmatrix. This test is not scored, as the dimension of the left null space\nis system-specific.\n\nImplementation:\nCalculate the left null space, i.e., the null space of the transposed\nstoichiometric matrix, using an algorithm based on the singular value\ndecomposition adapted from\nhttps://scipy.github.io/old-wiki/pages/Cookbook/RankNullspace.html\nThen, return the estimated dimension of that null space.","message":"The number of independent conservation relations is 36.","data":36,"format_type":"raw","metric":0.03896103896103896},"test_matrix_rank":{"duration":0.1273171039999852,"result":"passed","title":"Rank","summary":"The rank of the stoichiometric matrix is system specific. It is\ncalculated using singular value decomposition (SVD).\n\nImplementation:\nCompose the stoichiometric matrix, then estimate the rank, i.e. the\ndimension of the column space, of a matrix. The algorithm used by this\nfunction is based on the singular value decomposition of the matrix.","message":"The rank of the S-Matrix is 885.","data":885,"format_type":"raw","metric":0.8719211822660099},"test_degrees_of_freedom":{"duration":0.12402627500000563,"result":"passed","title":"Degrees Of Freedom","summary":"The degrees of freedom of the stoichiometric matrix, i.e., the number\nof 'free variables' is system specific and corresponds to the dimension\nof the (right) null space of the matrix.\n\nImplementation:\nCompose the stoichiometric matrix, then calculate the dimensionality of the\nnull space using the rank-nullity theorem outlined by\nAlama, J. The Rank+Nullity Theorem. Formalized Mathematics 15, (2007).","message":"The degrees of freedom of the S-Matrix are 130.","data":130,"format_type":"raw","metric":0.12807881773399016},"test_sbml_level":{"duration":0.00023092099996802062,"result":"passed","title":"SBML Level and Version","summary":"This test reports if the model file is represented in the latest edition\n(level) of the Systems Biology Markup Language (SBML) which is Level 3,\nand at least version 1.\n\nImplementation:\nThe level and version are parsed directly from the SBML document.","message":"The SBML file uses: SBML Level 3 Version 1","data":"SBML Level 3 Version 1","format_type":"raw","metric":0.0},"test_fbc_presence":{"duration":0.0001946440000324401,"result":"passed","title":"FBC enabled","summary":"The Flux Balance Constraints (FBC) Package extends SBML with structured\nand semantic descriptions for domain-specific model components such as\nflux bounds, multiple linear objective functions, gene-protein-reaction\nassociations, metabolite chemical formulas, charge and related annotations\nwhich are relevant for parameterized GEMs and FBA models. The SBML and\nconstraint-based modeling communities collaboratively develop this package\nand update it based on user input.\n\nImplementation:\nParse the state of the FBC plugin from the SBML document.","message":"The FBC package *is* used.","data":true,"format_type":"raw","metric":0.0},"test_metabolite_sbo_presence":{"duration":0.0021466409999675307,"result":"failed","title":"Metabolite General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Implementation:\n    Check if each cobra.Metabolite has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 156 metabolites (16.88%) lack annotation with any type\nof SBO term: tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","data":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.16883116883116883},"test_reaction_sbo_presence":{"duration":0.0024124870000150622,"result":"failed","title":"Reaction General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Implementation:\n    Check if each cobra.Reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 48 reactions (4.73%) lack annotation with any type\nof SBO term: SUCRt2, MOADSUx, MPTS, MOCOS, MPTAT, ...","data":["SUCRt2","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","MDH","FNOR","PC6YM","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","GLCP4","GLCP3"],"format_type":"count","metric":0.04729064039408867},"test_gene_sbo_presence":{"duration":0.001705628000024717,"result":"failed","title":"Gene General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Check if each cobra.Gene has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 97 genes (11.00%) lack annotation with any type of\nSBO term: cscB, Synpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211,\nSynpcc7942_1656, ...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_metabolic_reaction_specific_sbo_presence":{"duration":0.0010945250000418127,"result":"failed","title":"Metabolic Reaction SBO:0000176 Presence","summary":"    SBO:0000176 represents the term 'biochemical reaction'. Every metabolic\n    reaction that is not a transport or boundary reaction should be annotated\n    with this. The results shown are relative to the total amount of pure\n    metabolic reactions.\n\n    Implementation:\n    Check if each pure metabolic reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being the SBO term above.","message":"A total of 47 metabolic reactions (6.66% of all purely\nmetabolic reactions) lack annotation with the SBO term\n\"SBO:0000176\" for 'biochemical reaction': DRBK, MOCOS, MPTS, DPGM,\nMOADSUx, ...","data":["DRBK","MOCOS","MPTS","DPGM","MOADSUx","MPTAT","MPTSS","CPMPS","GTPC","MDH","FNOR","CYSTL","PC6YM","CSND","G1Dx","MOGDS","DRPA","LYCBC1","AMAA","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","GLCP4","GLCP3"],"format_type":"count","metric":0.06657223796033994},"test_transport_reaction_specific_sbo_presence":{"duration":0.0006989860000317094,"result":"failed","title":"Transport Reaction SBO:0000185 Presence","summary":"    'SBO:0000185', 'SBO:0000588', 'SBO:0000587', 'SBO:0000655', 'SBO:0000654',\n    'SBO:0000660', 'SBO:0000659', 'SBO:0000657', and 'SBO:0000658' represent\n    the terms 'transport reaction' and 'translocation reaction', in addition\n    to their children (more specific transport reaction labels). Every\n    transport reaction that is not a pure metabolic or boundary reaction should\n    be annotated with one of these terms. The results shown are relative to the\n    total of all transport reactions.\n\n    Implementation:\n    Check if each transport reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 1 metabolic reactions (0.81% of all transport\nreactions) lack annotation with one of the SBO terms: ['SBO:0000185',\n'SBO:0000588', 'SBO:0000587', 'SBO:0000655', 'SBO:0000654',\n'SBO:0000660', 'SBO:0000659', 'SBO:0000657', 'SBO:0000658'] for\n'biochemical reaction': SUCRt2","data":["SUCRt2"],"format_type":"count","metric":0.008130081300813009},"test_metabolite_specific_sbo_presence":{"duration":0.002048047000016595,"result":"failed","title":"Metabolite SBO:0000247 Presence","summary":"    SBO:0000247 represents the term 'simple chemical'. Every metabolite should\n    be annotated with this.\n\n    Implementation:\n    Check if each cobra.Metabolite has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 156 transport reactions (16.88% of all metabolites)\nlack annotation with the SBO term \"SBO:0000247\" for\n'simple chemical': tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","data":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.16883116883116883},"test_gene_specific_sbo_presence":{"duration":0.001835849999963557,"result":"failed","title":"Gene SBO:0000243 Presence","summary":"    SBO:0000243 represents the term 'gene'. Every gene should\n    be annotated with this.\n\n    Implementation:\n    Check if each cobra.Gene has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 97 genes (11.00% of all genes) lack             annotation\nwith the SBO term \"SBO:0000243\" for             'gene': cscB,\nSynpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211, Synpcc7942_1656,\n...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_exchange_specific_sbo_presence":{"duration":0.006253655000023173,"result":"failed","title":"Exchange Reaction SBO:0000627 Presence","summary":"    SBO:0000627 represents the term 'exchange reaction'. The Systems Biology\n    Ontology defines an exchange reaction as follows: 'A modeling process to\n    provide matter influx or efflux to a model, for example to replenish a\n    metabolic network with raw materials (eg carbon / energy sources). Such\n    reactions are conceptual, created solely for modeling purposes, and do not\n    have a  physical correspondence. Exchange reactions, often represented as\n    'R_EX_', can operate in the negative (uptake) direction or positive\n    (secretion) direction. By convention, a negative flux through an exchange\n    reaction represents uptake of the corresponding metabolite, and a positive\n    flux represent discharge.' Every exchange reaction should be annotated with\n    this. Exchange reactions differ from demand reactions in that the\n    metabolites are removed from or added to the extracellular\n    environment only.\n\n    Implementation:\n    Check if each exchange reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 exchange reactions (0.00% of all exchange\nreactions) lack annotation with the SBO term \"SBO:0000627\" for\n'exchange reaction':","data":[],"format_type":"count","metric":0.0},"test_demand_specific_sbo_presence":{"duration":0.005854559999988851,"result":"failed","title":"Demand Reaction SBO:0000628 Presence","summary":"    SBO:0000628 represents the term 'demand reaction'. The Systems Biology\n    Ontology defines a demand reaction as follows: 'A modeling process\n    analogous to exchange reaction, but which operates upon \"internal\"\n    metabolites. Metabolites that are consumed by these reactions are assumed\n    to be used in intra-cellular processes that are not part of the model.\n    Demand reactions, often represented 'R_DM_', can also deliver metabolites\n    (from intra-cellular processes that are not considered in the model).'\n    Every demand reaction should be annotated with\n    this. Demand reactions differ from exchange reactions in that the\n    metabolites are not removed from the extracellular environment, but from\n    any of the organism's compartments. Demand reactions differ from sink\n    reactions in that they are designated as irreversible.\n\n    Implementation:\n    Check if each demand reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 genes (0.00% of all demand reactions) lack\nannotation with the SBO term \"SBO:0000628\" for             'demand\nreaction':","data":[],"format_type":"count","metric":0.0},"test_sink_specific_sbo_presence":{"duration":0.005929309000009653,"result":"failed","title":"Sink Reactions SBO:0000632 Presence","summary":"    SBO:0000632 represents the term 'sink reaction'. The Systems Biology\n    Ontology defines a sink reaction as follows: 'A modeling process to\n    provide matter influx or efflux to a model, for example to replenish a\n    metabolic network with raw materials (eg carbon / energy sources). Such\n    reactions are conceptual, created solely for modeling purposes, and do not\n    have a physical correspondence. Unlike the analogous demand (SBO:....)\n    reactions, which are usually designated as irreversible, sink reactions\n    always represent a reversible uptake/secretion processes, and act as a\n    metabolite source with no cost to the cell. Sink reactions, also referred\n    to as R_SINK_, are generally used for compounds that are metabolized by\n    the cell but are produced by non-metabolic, un-modeled cellular processes.'\n    Every sink reaction should be annotated with\n    this. Sink reactions differ from exchange reactions in that the metabolites\n    are not removed from the extracellular environment, but from any of the\n    organism's compartments.\n\n    Implementation:\n    Check if each sink reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 genes (0.00% of all sink reactions) lack\nannotation with the SBO term \"SBO:0000632\" for         'sink\nreaction':","data":[],"format_type":"count","metric":0.0},"test_biomass_specific_sbo_presence":{"duration":0.00032654000000320593,"result":"passed","title":"Biomass Reactions SBO:0000629 Presence","summary":"    SBO:0000629 represents the term 'biomass production'. The Systems Biology\n    Ontology defines an exchange reaction as follows: 'Biomass production,\n    often represented 'R_BIOMASS_', is usually the optimization target reaction\n    of constraint-based models, and can consume multiple reactants to produce\n    multiple products. It is also assumed that parts of the reactants are also\n    consumed in unrepresented processes and hence products do not have to\n    reflect all the atom composition of the reactants. Formulation of a\n    biomass production process entails definition of the macromolecular\n    content (eg. cellular protein fraction), metabolic constitution of\n    each fraction (eg. amino acids), and subsequently the atomic composition\n    (eg. nitrogen atoms). More complex biomass functions can additionally\n    incorporate details of essential vitamins and cofactors required for\n    growth.'\n    Every reaction representing the biomass production should be annotated with\n    this.\n\n    Implementation:\n    Check if each biomass reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 biomass reactions (0.00% of all biomass reactions)\nlack annotation with the SBO term \"SBO:0000629\" for         'biomass\nproduction':","data":[],"format_type":"count","metric":0.0}},"score":{"sections":[{"section":"consistency","score":0.5407620092558443},{"section":"annotation_met","score":0.7531998804511668},{"section":"annotation_rxn","score":0.783415435139573},{"section":"annotation_gene","score":0.33000755857898717},{"section":"annotation_sbo","score":0.9382172776505766}],"total_score":0.7246901155700989},"cards":{"scored":{"title":"Core Tests","sections":{"consistency":{"title":"Consistency","weight":3.0,"cases":["test_stoichiometric_consistency","test_reaction_mass_balance","test_reaction_charge_balance","test_find_disconnected","test_find_reactions_unbounded_flux_default_condition"]},"annotation_met":{"title":"Annotation - Metabolites","weight":1.0,"cases":["test_metabolite_annotation_presence","test_metabolite_annotation_overview","test_metabolite_annotation_wrong_ids","test_metabolite_id_namespace_consistency"]},"annotation_rxn":{"title":"Annotation - Reactions","weight":1.0,"cases":["test_reaction_annotation_presence","test_reaction_annotation_overview","test_reaction_annotation_wrong_ids","test_reaction_id_namespace_consistency"]},"annotation_gene":{"title":"Annotation - Genes","weight":1.0,"cases":["test_gene_product_annotation_presence","test_gene_product_annotation_overview","test_gene_product_annotation_wrong_ids"]},"annotation_sbo":{"title":"Annotation - SBO Terms","weight":2.0,"cases":["test_metabolite_sbo_presence","test_metabolite_specific_sbo_presence","test_reaction_sbo_presence","test_metabolic_reaction_specific_sbo_presence","test_transport_reaction_specific_sbo_presence","test_exchange_specific_sbo_presence","test_demand_specific_sbo_presence","test_sink_specific_sbo_presence","test_gene_sbo_presence","test_gene_specific_sbo_presence","test_biomass_specific_sbo_presence"]}}},"sbml_format":{"title":"SBML","cases":["test_sbml_level","test_fbc_presence"]},"basic_info":{"title":"Basic Information","cases":["test_model_id_presence","test_metabolites_presence","test_reactions_presence","test_genes_presence","test_compartments_presence","test_metabolic_coverage","test_unconserved_metabolites","test_inconsistent_min_stoichiometry"]},"basic_met":{"title":"Metabolite Information","cases":["test_find_unique_metabolites","test_find_duplicate_metabolites_in_compartments","test_metabolites_charge_presence","test_metabolites_formula_presence","test_find_medium_metabolites"]},"basic_rxn":{"title":"Reaction Information","cases":["test_find_pure_metabolic_reactions","test_find_constrained_pure_metabolic_reactions","test_find_transport_reactions","test_find_constrained_transport_reactions","test_find_candidate_irreversible_reactions","test_find_reactions_with_partially_identical_annotations","test_find_duplicate_reactions","test_find_reactions_with_identical_genes"]},"gpr_calculations":{"title":"Gene-Protein-Reaction (GPR) Associations","cases":["test_gene_protein_reaction_rule_presence","test_transport_reaction_gpr_presence","test_protein_complex_presence"]},"test_biomass":{"title":"Biomass","cases":["test_biomass_presence","test_biomass_consistency","test_biomass_default_production","test_fast_growth_default","test_biomass_open_production","test_biomass_precursors_default_production","test_biomass_precursors_open_production","test_direct_metabolites_in_biomass","test_essential_precursors_not_in_biomass"]},"energy_metabolism":{"title":"Energy Metabolism","cases":["test_ngam_presence","test_gam_in_biomass","test_find_reversible_oxygen_reactions","test_detect_energy_generating_cycles"]},"gap_finding":{"title":"Network Topology","cases":["test_blocked_reactions","test_find_orphans","test_find_deadends","test_find_stoichiometrically_balanced_cycles","test_find_metabolites_not_produced_with_open_bounds","test_find_metabolites_not_consumed_with_open_bounds"]},"matrix":{"title":"Matrix Conditioning","cases":["test_absolute_extreme_coefficient_ratio","test_number_independent_conservation_relations","test_matrix_rank","test_degrees_of_freedom"]},"experimental":{"title":"Experimental Data Comparison","cases":["test_growth_from_data_qualitative","test_gene_essentiality_from_data_qualitative"]},"misc":{"title":"Misc. Tests","cases":["test_excreted"]}},"weights":{"test_reaction_mass_balance":1.0,"test_find_disconnected":1.0,"test_stoichiometric_consistency":3.0,"test_reaction_charge_balance":1.0,"test_metabolite_annotation_presence":1.0,"test_reaction_annotation_presence":1.0,"test_metabolite_annotation_overview":1.0,"test_reaction_annotation_overview":1.0,"test_metabolite_annotation_wrong_ids":1.0,"test_reaction_annotation_wrong_ids":1.0,"test_metabolite_id_namespace_consistency":1.0,"test_reaction_id_namespace_consistency":1.0}};
+    window.data = {"meta":{"timestamp":"2024-04-16 18:50:23.982351","platform":"Linux","release":"6.5.0-1017-azure","python":"3.10.6","packages":{"click":"8.1.7","click-configfile":"0.2.3","click-log":"0.4.0","six":"1.16.0","future":"1.0.0","pytest":"7.4.4","gitpython":"3.1.43","pygithub":"1.59.1","pandas":"2.2.2","jinja2":"3.1.3","cookiecutter":"2.6.0","cobra":"0.29.0","ruamel.yaml":"0.18.6","sympy":"1.12","sqlalchemy":"2.0.29","requests":"2.31.0","numpydoc":"1.7.0","pylru":"1.2.1","pandera":"0.18.3","jsonschema":"4.21.1","depinfo":"2.2.0","importlib-resources":"6.4.0","black":"not installed","isort":"not installed","tox":"not installed"}},"tests":{"test_excreted":{"duration":3.665218698999979,"result":"failed","title":"Models ability to excrete metabolites","summary":"This test addresses the models ability to excrete metabolites.\nModels are optimized to produce the given exchange reaction and\nsimulated with natural medium.","message":"Model is able to excrete 1 and unable to          excrete 16","data":{"TP":["sucr"],"FN":["3pg","acac","acmana","arab__D","arbt","bhb","g15lac","gam1p","glc__D","lcts","malt","phyt","pnto__R","pro__L","pyr","rib__D"]},"format_type":"number","metric":16},"test_metabolite_annotation_presence":{"duration":0.0006939319999901272,"result":"failed","title":"Presence of Metabolite Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field for each metabolite, irrespective of the type of\nannotation i.e. specific database  cross-references, ontology terms,\nadditional information. For this test to pass the model is expected to\nhave metabolites and each of them should have some form of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Metabolite object of the\nmodel is unset or empty.","message":"A total of 31 metabolites (3.35%) lack any form of annotation:\n38ch2gtp_c, gcaro_c, lyc_c, mocogdp_c, acmama_c, ...","data":["38ch2gtp_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.03354978354978355},"test_reaction_annotation_presence":{"duration":0.0008810530000005201,"result":"failed","title":"Presence of Reaction Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field for each reaction, irrespective of the type of\nannotation i.e. specific database  cross-references, ontology terms,\nadditional information. For this test to pass the model is expected to\nhave reactions and each of them should have some form of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Reaction object of the\nmodel is unset or empty.","message":"A total of 38 reactions (3.74%) lack any form of annotation:\nGTPC, LYCBC1, MOGDS, AMAA, CSND, ...","data":["GTPC","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","GLCP4","GLCP3"],"format_type":"count","metric":0.0374384236453202},"test_gene_product_annotation_presence":{"duration":0.0004948089999743388,"result":"failed","title":"Presence of Gene Annotation","summary":"This test checks if any annotations at all are present in the SBML\nannotations field (extended by FBC package) for each gene product,\nirrespective of the type of annotation i.e. specific database,\ncross-references, ontology terms, additional information. For this test to\npass the model is expected to have genes and each of them should have some\nform of annotation.\n\nImplementation:\nCheck if the annotation attribute of each cobra.Gene object of the\nmodel is unset or empty.","message":"A total of 97 genes (11.00%) lack any form of         annotation:\ncscB, Synpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211,\nSynpcc7942_1656, ...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_metabolite_annotation_overview":{"duration":{"pubchem.compound":0.0006402409999850533,"kegg.compound":0.0005445820000318236,"seed.compound":0.0005397929999730877,"inchikey":0.0005196150000301714,"inchi":0.0005077630000300815,"chebi":0.0005049769999914133,"hmdb":0.0005058190000113427,"reactome":0.0005193640000129562,"metanetx.chemical":0.0004356169999937265,"bigg.metabolite":0.0004608339999663258,"biocyc":0.00047930900001347254},"result":{"pubchem.compound":"failed","kegg.compound":"failed","seed.compound":"failed","inchikey":"failed","inchi":"failed","chebi":"failed","hmdb":"failed","reactome":"failed","metanetx.chemical":"failed","bigg.metabolite":"failed","biocyc":"failed"},"title":"Metabolite Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each metabolite annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all metabolites consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Metabolite of\nthe model match with a selection of common biochemical databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"pubchem.compound":"The following 924 metabolites (100.00%) lack annotation for\npubchem.compound:         dhf_c, dudp_c, 3omrsACP_c, trnaglu_c,\npre6a_c, ...","kegg.compound":"The following 341 metabolites (36.90%) lack annotation for\nkegg.compound:         ugmd_c, 3a2oxpp_c, amylose_c, hdeACP_c, pcox_u,\n...","seed.compound":"The following 289 metabolites (31.28%) lack annotation for\nseed.compound:         ugmd_c, 3a2oxpp_c, amylose_c, hdeACP_c,\nphycy_c, ...","inchikey":"The following 924 metabolites (100.00%) lack annotation for inchikey:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","inchi":"The following 924 metabolites (100.00%) lack annotation for inchi:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","chebi":"The following 235 metabolites (25.43%) lack annotation for chebi:\n3a2oxpp_c, amylose_c, hdeACP_c, pcox_u, octe9ACP_c, ...","hmdb":"The following 509 metabolites (55.09%) lack annotation for hmdb:\n3omrsACP_c, trnaglu_c, pre6a_c, 3hhexACP_c, glyald_c, ...","reactome":"The following 924 metabolites (100.00%) lack annotation for reactome:\ndhf_c, dudp_c, 3omrsACP_c, trnaglu_c, pre6a_c, ...","metanetx.chemical":"The following 247 metabolites (26.73%) lack annotation for\nmetanetx.chemical:         3a2oxpp_c, amylose_c, phycy_c, bm_pigm_c,\nu3hga2_c, ...","bigg.metabolite":"The following 156 metabolites (16.88%) lack annotation for\nbigg.metabolite:         tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","biocyc":"The following 356 metabolites (38.53%) lack annotation for biocyc:\n3hhexACP_c, db4p_c, ugmd_c, 3a2oxpp_c, tdec2eACP_c, 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Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each reaction annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all reactions consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Reaction of\nthe model match with a selection of common biochemical databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"rhea":"The following 605 reactions (59.61%) lack annotation for rhea:\nEX_gln__L_e, O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1, ...","kegg.reaction":"The following 624 reactions (61.48%) lack annotation for\nkegg.reaction:         EX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e,\nO2tcx, ...","seed.reaction":"The following 520 reactions (51.23%) lack annotation for\nseed.reaction:         O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1,\nHISTDa, ...","metanetx.reaction":"The following 411 reactions (40.49%) lack annotation for\nmetanetx.reaction:         O2tcx, AOXPBDC, BIOMASS_PIGMENTS,\nBIOMASS__1, HISTDa, ...","bigg.reaction":"The following 166 reactions (16.35%) lack annotation for\nbigg.reaction:         EX_tre_e, EX_man_e, EX_galt_e, EX_arab__L_e,\nEX_acgam_e, ...","reactome":"The following 1015 reactions (100.00%) lack annotation for reactome:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, ADPT, ...","ec-code":"The following 544 reactions (53.60%) lack annotation for ec-code:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, O2tcx, ...","brenda":"The following 1015 reactions (100.00%) lack annotation for brenda:\nEX_gln__L_e, EX_hco3_e, EX_mn2_e, EX_arg__L_e, ADPT, ...","biocyc":"The following 606 reactions (59.70%) lack annotation for biocyc:\nEX_hco3_e, O2tcx, AOXPBDC, BIOMASS_PIGMENTS, BIOMASS__1, ..."},"data":{"rhea":["EX_gln__L_e","O2tcx","AOXPBDC","BIOMASS_PIGMENTS","BIOMASS__1","ACOATA","3HAD160","RNDR3","HISTDa","DMBZIDS2","ZCAROTDH2","CMPA_1","U23GAAT2","HOXGfx","LPOR","GCALDDy","MSBENZMT","DESAT18a","PHYFXOR","TMPPP_1","RNDR1","HEMEAS_1","DHORD3um","HBZNPT","COCHL_1","HISTDb","H4THDPR","GLCS3","PRAGSr","UDCPDPS","G1PACT","3HAD60","PGI","KAS14","PQH2tum","O2tu","O2tpp","3HAD80","3OAR160","PPK","PHYTES2_1","GLUSfx","GLUTRR","PSIum","FOLD3","MEHLER_1","3OAS140","PPK2","IPDPS_syn","GLYDHDA","H4THDPS","EAR60y","ADOCBLS","PDS2_1","O2tex","GF6PTA","PGMT","GLCP2_1","AGDI_1","LPADSS2","EX_ptrc_e","EAR120y","HEX7","CYTBD4cm","PRE3BS","PPPGO2_1","BIOMASS_DNA","DNAMTn2r","BIOMASS_CELL_WALL","RB15BPtcx","3HAD180","3OAS80","AMPMS3","G1PCTYT","UHGADA2","DHNANT","HGYDAS","3PGtcx","PAPSR","BIOMASS_COFACTORS","DM_h2_c","DPOR","3HAD140","ARGOXRum","BCAROHX2","HPPK","GTPCII","GLCBRAN3","DB4PS","RBFSa","GLUTRS","EAR160y","PDX5PS2","KARI_23dhmp_1","ASPOb","RBFSb_1","SUCDum","DVOCHR_1","H2CO3_NAt_syn","MPOMT_1","PC17M_1","NDHPQRum","CYNL","CYOOum","BPNT2","FNOR_1","DMTPHT","PC6YM_1","CYRDAAT","MECDPDHf","Htcx","3HAD40_2","ZCAROTDH1","CYRDAR","BIOMASS_MEM_LIPIDS","HCO3tcx","GLYALDDy","BIOMASS_PROTEIN","3OAR40_2","RNDR2","NPDPS","3OAS100","MAN6PI","HPROb","3OAS120","EAR180y","3OAS60","EAR40y","TKT1","PKETF","NDHPQRcm","TRDR","NTRIRfx","DHNCOAS","MCOATA","PKETX","PMPK","HTHRPDH","UAGAAT2","PRPPS","CITMS","BCT1_syn","TRDRf","ADCYRS","PC6AR_1","TRSARyr","CYNTtabcpp","RBPCcx","DHNPA_1","BIOMASS_RNA","DM_dialurate_c","CO2tex","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","PQH2tcm","2PGLYCtcx","PDS1_1","3OAS180","EAR80y","DM_5drib_c","SK_amylose_c","EAR140y","CYTBD4um","DHPPDA","BCAROHX","SK_14glucan_c","SK_glycogen_c","EX_o2_e","EX_co2_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","UAAGDS","ARGDHpp","DMPPS_syn","ANS2","3OAS160","ACHBSb","MPOMOR_1","EX_cynt_e","AHSERL2_1","PEPC","NTRARf2","G6PDA","Nat_Kpp","CA2t2pp","SULR_2","UGMDDS","GLCDBRAN3","RPI","FMNRy_1","PGPP_OLE_PALM","H2Otcx","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","DM_amob_c","OPMEACPD","OPMEACPR","EX_photon530_e","EX_photon550_e","AGPAT160","EX_photon570_e","EX_photon590_e","EX_photon610_e","AGPATACP_HDE_PALM","LEUtex","BTS6","QUERT","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","GLNtex","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","CYNTtex","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","GLUDGS_HDE_HDE","TYRTRS","DAGK160","DAGK_HDE_PALM","DAGK161","SQDGS_PALM_PALM","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","PTRCtex","DGDGS_HDE_HDE","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","PROTRS","GLYTRS","CYSTRS","ARGTRS","TRPTRS","HISTRS","CO2tpp","PHETRS","ASNTRS","ASPTRS","THRTRS","LEUTRS","ILETRS","CHLADMT_1","LYSTRS","AOXSr2","LIPOS2","ALATRS","TRNFE","VALTRS","FMETTRS","BACCL","BTNPL2","LIPAMPL_1","LIPOCT","LIPATPT_1","ZXANHX","PHOA410um","PHOA430um","OGMEACPR","PHOA450um","PHOA470um","PHOA490um","PHOA510um","PHOA530um","PLYCOI","PHOA550um","SAMTRI","EPXQR","PHOA570um","PHOA590um","PHOA610um","ZCARDS","PHOA630um","PHOA650um","PHOA670um","PHOA690um","DM_pho_loss_c","ETCHLAS","ETBCARO","COLIPAabcex","MLDCP1App","CDPGLC46DH","AACPS6","ALDR18","ALDDC17","THZT","MLDCP1Bpp","PHYPQOX","MLDCP2App","MLDCP2Bpp","AGM4Pt2pp","AGMt2pp","CXANHX","OGMEACPS","EGMEACPR","DXYTST","OANTS","ACGAMT","Htabcpp","ETAPCPSII","STCHLPSIum","DEXZEAX","PFOR","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","GLYCOX1","UM4PL","UM3PL","PAPPT3","OANTIabcpp","OANTILpp","MDDCP1pp","MDDCP2pp","STACPSI","MLTGY1pp","ETCPC","GLYCOX2","NO2tabcpp","MLTGY2pp","MLTGY3pp","MLTGY4pp","AGM4PA","AM3PA","AM4PA","SK_fum_c","DM_succ_c","AGM3PApp","AGM4PApp","UM4PCP","SK_akg_c","NGAM_D1um","PSICRum","AM4PCP","4PCP","AGM4PCP","AGMH","PSIICRum","DM_ac_c","AGM3PH","DM_lac__D_c","NGAM","AGM4PH","LADGMDH","CELLSYN","ALAALAabcpp","4PEPTabcpp","ADPGLC","DALAabcpp","ZISO","3OAR180","3OAR140","PAPA160","PHEOASE","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","MCTP2App","MCTP1App","MCTP1Bpp","ACLSa","PAPA_OLE_PALM","ACLSb","PHEOX_1","OPMEACPS","EAR100y","EHGLAT","KAS15","PHYTK","NDH_1_4_um_copy2","KARI_1","3HAD120","OGMEACPD","CITCIa","DAGK_OLE_HDE","DAGK_OLE_PALM","3HAD100","3OAR120","3OAR60","3OAR100","3OAR80","NDH_1_1_um_copy1","NDH_1_4_um_copy1","PCHLDA430","PCHLDA650","GGCLUT2","ANHMK","RNDR4","PSICSum","CBFCum","SUCR","CLt3_1pp","Ktu","THBTGT","FDH6","PCXHtpp","THISAT","PSIIum","ATPSum","CYSDES","MDDEP1pp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","MDDCP3pp","MDDCP4pp","MDDCP5pp","MDDEP2pp","MDDEP3pp","MDDEP4pp","MNHNAtpp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX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tion":0.40492610837438425,"bigg.reaction":0.16354679802955666,"reactome":1.0,"ec-code":0.5359605911330049,"brenda":1.0,"biocyc":0.5970443349753695},"score":{"rhea":0.40394088669950734,"kegg.reaction":0.38522167487684733,"seed.reaction":0.48768472906403937,"metanetx.reaction":0.5950738916256157,"bigg.reaction":0.8364532019704434,"reactome":0.0,"ec-code":0.46403940886699513,"brenda":0.0,"biocyc":0.40295566502463054}},"test_gene_product_annotation_overview":{"duration":{"refseq":0.000521528000035687,"uniprot":0.00046455199998263197,"ecogene":0.00047372899996389606,"kegg.genes":0.00046985200003746286,"ncbigi":0.0003908829999659247,"ncbigene":0.0004924240000150348,"ncbiprotein":0.00046816899998702866,"ccds":0.00046858899997914705,"hprd":0.00047161399999140485,"asap":0.0004635399999983747},"result":{"refseq":"failed","uniprot":"failed","ecogene":"failed","kegg.genes":"failed","ncbigi":"failed","ncbigene":"failed","ncbiprotein":"failed","ccds":"failed","hprd":"failed","asap":"failed"},"title":"Gene Annotations Per Database","summary":"Specific database cross-references are paramount to mapping information.\nTo provide references to as many databases as possible helps to make the\nmetabolic model more accessible to other researchers. This does not only\nfacilitate the use of a model in a broad array of computational pipelines,\nit also promotes the metabolic model itself to become an organism-specific\nknowledge base.\n\nFor this test to pass, each gene annotation should contain\ncross-references to a number of databases. The currently selection is\nlisted in `annotation.py`, but an ongoing discussion can be found at\nhttps://github.com/opencobra/memote/issues/332. For each database this\ntest checks for the presence of its corresponding namespace ID to comply\nwith the MIRIAM guidelines i.e. they have to match those defined on\nhttps://identifiers.org/.\n\nSince each database is quite different and some potentially incomplete, it\nmay not be feasible to achieve 100% coverage for each of them. Generally\nit should be possible, however, to obtain cross-references to at least\none of the databases for all gene products consistently.\n\nImplementation:\nCheck if the keys of the annotation attribute of each cobra.Gene of\nthe model match with a selection of common genome databases. The\nannotation  attribute of cobrapy components is a dictionary of\nkey:value pairs.","message":{"refseq":"The following 882 genes (100.00%) lack annotation for refseq:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","uniprot":"The following 882 genes (100.00%) lack annotation for uniprot:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ecogene":"The following 882 genes (100.00%) lack annotation for ecogene:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","kegg.genes":"The following 882 genes (100.00%) lack annotation for kegg.genes:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbigi":"The following 113 genes (12.81%) lack annotation for ncbigi:\nSYNPCC7942_RS12985, Synpcc7942_2454, SYNPCC7942_RS03125,\nSynpcc7942_0034, Synpcc7942_0413, ...","ncbigene":"The following 882 genes (100.00%) lack annotation for ncbigene:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbiprotein":"The following 882 genes (100.00%) lack annotation for ncbiprotein:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ccds":"The following 882 genes (100.00%) lack annotation for ccds:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","hprd":"The following 882 genes (100.00%) lack annotation for hprd:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","asap":"The following 882 genes (100.00%) lack annotation for asap:\nSYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ..."},"data":{"refseq":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS12985","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","Synpcc7942_2454","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS03125","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","Synpcc7942_0034","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","Synpcc7942_0413","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13375","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7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Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in metabolite annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those metabolites whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"pubchem.compound":"There are no metabolite annotations for the pubchem.compound database.","kegg.compound":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nkegg.compound         database:","seed.compound":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nseed.compound         database:","inchikey":"There are no metabolite annotations for the inchikey database.","inchi":"There are no metabolite annotations for the inchi database.","chebi":"A total of 117 metabolite annotations (16.98%) do not match the\nregular expression patterns defined on identifiers.org for the chebi\ndatabase: tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","hmdb":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the hmdb\ndatabase:","reactome":"There are no metabolite annotations for the reactome database.","metanetx.chemical":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nmetanetx.chemical         database:","bigg.metabolite":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nbigg.metabolite         database:","biocyc":"A total of 0 metabolite annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the biocyc\ndatabase:"},"data":{"pubchem.compound":[],"kegg.compound":[],"seed.compound":[],"inchikey":[],"inchi":[],"chebi":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","mpt_c","moco_c","mptamp_c","fdxo_2_2_c"],"hmdb":[],"reactome":[],"metanetx.chemical":[],"bigg.metabolite":[],"biocyc":[]},"format_type":"percent","metric":{"pubchem.compound":1.0,"kegg.compound":0.0,"seed.compound":0.0,"inchikey":1.0,"inchi":1.0,"chebi":0.16981132075471697,"hmdb":0.0,"reactome":1.0,"metanetx.chemical":0.0,"bigg.metabolite":0.0,"biocyc":0.0},"score":{"pubchem.compound":0.0,"kegg.compound":1.0,"seed.compound":1.0,"inchikey":0.0,"inchi":0.0,"chebi":0.8301886792452831,"hmdb":1.0,"reactome":0.0,"metanetx.chemical":1.0,"bigg.metabolite":1.0,"biocyc":1.0}},"test_reaction_annotation_wrong_ids":{"duration":{"rhea":0.0016388440000127957,"kegg.reaction":0.0009618650000220441,"seed.reaction":0.001079896000021563,"metanetx.reaction":0.0010825809999914782,"bigg.reaction":0.00114953700000342,"reactome":0.00046555400001579983,"ec-code":0.001376101000005292,"brenda":0.00045350100003815896,"biocyc":0.0009701289999952678},"result":{"rhea":"failed","kegg.reaction":"passed","seed.reaction":"passed","metanetx.reaction":"passed","bigg.reaction":"passed","reactome":"failed","ec-code":"failed","brenda":"failed","biocyc":"passed"},"title":"Reaction Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in reaction annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those reaction whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"rhea":"A total of 20 reaction annotations (1.97%) do not match the\nregular expression patterns defined on identifiers.org for the rhea\ndatabase: Cobalt2abcppI, SPMDabcpp, CA2abcpp, ARGabcpp, MNabc_1, ...","kegg.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nkegg.reaction         database:","seed.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nseed.reaction         database:","metanetx.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nmetanetx.reaction         database:","bigg.reaction":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the\nbigg.reaction         database:","reactome":"There are no reaction annotations for the reactome database.","ec-code":"A total of 16 reaction annotations (1.58%) do not match the\nregular expression patterns defined on identifiers.org for the ec-code\ndatabase: HEMEAS_1, UDCPDPS, PFK_3, DNMPPA, PPNCL3, ...","brenda":"There are no reaction annotations for the brenda database.","biocyc":"A total of 0 reaction annotations (0.00%) do not match the\nregular expression patterns defined on identifiers.org for the biocyc\ndatabase:"},"data":{"rhea":["Cobalt2abcppI","SPMDabcpp","CA2abcpp","ARGabcpp","MNabc_1","MG2uabcpp","PTRCabcpp","NI2uabcpp","Kabcpp","CUabcpp","MOBDabcpp","FE3abcpp","PIuabcpp","LEUabcpp","SULabcpp","NO3abcpp","GLNabcpp","MPTAT","MDH","PC6YM"],"kegg.reaction":[],"seed.reaction":[],"metanetx.reaction":[],"bigg.reaction":[],"reactome":[],"ec-code":["HEMEAS_1","UDCPDPS","PFK_3","DNMPPA","PPNCL3","HPYRRy","PROAKGOX1","CA2abcpp","FBA3","GLUTRS","GART","GTHRDH_syn","PDH","IG3PS","FALDH2","ASPO5"],"brenda":[],"biocyc":[]},"format_type":"percent","metric":{"rhea":0.019704433497536946,"kegg.reaction":0.0,"seed.reaction":0.0,"metanetx.reaction":0.0,"bigg.reaction":0.0,"reactome":1.0,"ec-code":0.015763546798029555,"brenda":1.0,"biocyc":0.0},"score":{"rhea":0.9802955665024631,"kegg.reaction":1.0,"seed.reaction":1.0,"metanetx.reaction":1.0,"bigg.reaction":1.0,"reactome":0.0,"ec-code":0.9842364532019704,"brenda":0.0,"biocyc":1.0}},"test_gene_product_annotation_wrong_ids":{"duration":{"refseq":0.0003567400000292764,"uniprot":0.0003536030000077517,"ecogene":0.00036069599997290425,"kegg.genes":0.0003499460000284671,"ncbigi":0.000982163000003311,"ncbigene":0.0003544549999787705,"ncbiprotein":0.00036885199995140283,"ccds":0.00035387299999456445,"hprd":0.00038854900003570947,"asap":0.0003504480000060539},"result":{"refseq":"failed","uniprot":"failed","ecogene":"failed","kegg.genes":"failed","ncbigi":"failed","ncbigene":"failed","ncbiprotein":"failed","ccds":"failed","hprd":"failed","asap":"failed"},"title":"Gene Annotation Conformity Per Database","summary":"To identify databases and the identifiers belonging to them, computational\ntools rely on the presence of specific patterns. Only when these patterns\ncan be identified consistently is an ID truly machine-readable. This test\nchecks if the database cross-references in reaction annotations conform\nto patterns defined according to the MIRIAM guidelines, i.e. matching\nthose that are defined at https://identifiers.org/.\n\nThe required formats, i.e., regex patterns are further outlined in\n`annotation.py`. This test does not carry out a web query for the composed\nURI, it merely controls that the regex patterns match the identifiers.\n\nImplementation:\nFor those genes whose annotation keys match any of the tested\ndatabases, check if the corresponding values match the identifier pattern\nof each database.","message":{"refseq":"There are no gene annotations for the refseq database.","uniprot":"There are no gene annotations for the uniprot database.","ecogene":"There are no gene annotations for the ecogene database.","kegg.genes":"There are no gene annotations for the kegg.genes database.","ncbigi":"A total of 769 gene annotations (87.19%) do not match the\nregular expression patterns defined on identifiers.org for the ncbigi\ndatabase: SYNPCC7942_RS07560, SYNPCC7942_RS12325, SYNPCC7942_RS07410,\nSYNPCC7942_RS00575, SYNPCC7942_RS03625, ...","ncbigene":"There are no gene annotations for the ncbigene database.","ncbiprotein":"There are no gene annotations for the ncbiprotein database.","ccds":"There are no gene annotations for the ccds database.","hprd":"There are no gene annotations for the hprd database.","asap":"There are no gene annotations for the asap database."},"data":{"refseq":[],"uniprot":[],"ecogene":[],"kegg.genes":[],"ncbigi":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7942_RS09290","SYNPCC7942_RS12700","SYNPCC7942_RS00460","S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Metabolite Identifier Namespace","summary":"In well-annotated models it is no problem if the pool of main identifiers\nfor metabolites consists of identifiers from several databases. However,\nin models that lack appropriate annotations, it may hamper the ability of\nother researchers to use it. Running the model through a computational\npipeline may be difficult without first consolidating the namespace.\n\nHence, this test checks if the main metabolite identifiers can be\nattributed to one single namespace based on the regex patterns defined at\nhttps://identifiers.org/\n\nImplementation:\nGenerate a table with each column corresponding to one\ndatabase from the selection and each row to a metabolite identifier. A\nBoolean entry indicates whether the identifier matches the regular\nexpression of the corresponding database. Since the Biocyc pattern matches\nbroadly, we assume that any instance of an identifier matching to Biocyc\nAND any other database pattern is a false positive match for Biocyc and\nthus set it to ``false``. Sum the positive matches for each database and\nassume that the largest set is the 'main' identifier namespace.","message":"1 metabolite identifiers (0.11%) deviate from the largest found\nnamespace (bigg.metabolite): cyst-L_c","data":["cyst-L_c"],"format_type":"count","metric":0.0010822510822510823},"test_reaction_id_namespace_consistency":{"duration":0.007037232000016047,"result":"passed","title":"Uniform Reaction Identifier Namespace","summary":"In well-annotated models it is no problem if the pool of main identifiers\nfor reactions consists of identifiers from several databases. However,\nin models that lack appropriate annotations, it may hamper the ability of\nother researchers to use it. Running the model through a computational\npipeline may be difficult without first consolidating the namespace.\n\nHence, this test checks if the main reaction identifiers can be\nattributed to one single namespace based on the regex patterns defined at\nhttps://identifiers.org/\n\nImplementation:\nGenerate a pandas.DataFrame with each column corresponding to one\ndatabase from the selection and each row to the reaction ID. A boolean\nentry indicates whether the metabolite ID matches the regex pattern\nof the corresponding database. Since the Biocyc pattern matches quite,\nassume that any instance of an identifier matching to Biocyc\nAND any other DB pattern is a false positive match for Biocyc and then set\nthe boolean to ``false``. Sum the positive matches for each database and\nassume that the largest set is the 'main' identifier namespace.","message":"0 reaction identifiers (0.00%) deviate from the largest found\nnamespace (bigg.reaction):","data":[],"format_type":"count","metric":0.0},"test_model_id_presence":{"duration":0.0001370460000202911,"result":"passed","title":"Model Identifier","summary":"The MIRIAM guidelines require a model to be identified via an ID.\nFurther, the ID will be displayed on the memote snapshot\nreport, which helps to distinguish the output clearly.\n\nImplementation:\nCheck if the cobra.Model object has a non-empty \"id\"\nattribute, this value is parsed from the \"id\" attribute of the <model> tag\nin the SBML file e.g. <model fbc:strict=\"true\" id=\"iJO1366\">.","message":"The model ID is syn_elong","data":"syn_elong","format_type":"raw","metric":0.0},"test_genes_presence":{"duration":0.00022995099999434387,"result":"passed","title":"Total Genes","summary":"A metabolic model can still be a useful tool without any\ngenes, however there are certain methods which rely on the presence of\ngenes and, more importantly, the corresponding gene-protein-reaction\nrules. This test requires that there is at least one gene defined.\n\nImplementation:\nCheck if the cobra.Model object has non-empty \"genes\"\nattribute, this list is populated from the list of fbc:listOfGeneProducts\nwhich should contain at least one fbc:geneProduct.","message":"882 genes are defined in the model.","data":["SYNPCC7942_RS07560","SYNPCC7942_RS12325","SYNPCC7942_RS07410","SYNPCC7942_RS00575","SYNPCC7942_RS03625","SYNPCC7942_RS05285","SYNPCC7942_RS13255","SYNPCC7942_RS13265","SYNPCC7942_RS13260","SYNPCC7942_RS11755","SYNPCC7942_RS11855","SYNPCC7942_RS11850","SYNPCC7942_RS06310","SYNPCC7942_RS07020","SYNPCC7942_RS02420","SYNPCC7942_RS05015","SYNPCC7942_RS05020","SYNPCC7942_RS03055","SYNPCC7942_RS06315","SYNPCC7942_RS03015","SYNPCC7942_RS00540","SYNPCC7942_RS05635","SYNPCC7942_RS13015","SYNPCC7942_RS07765","SYNPCC7942_RS04180","SYNPCC7942_RS05170","SYNPCC7942_RS12725","SYNPCC7942_RS06825","SYNPCC7942_RS11515","SYNPCC7942_RS06275","SYNPCC7942_RS05900","SYNPCC7942_RS02075","SYNPCC7942_RS06760","SYNPCC7942_RS11475","SYNPCC7942_RS04735","SYNPCC7942_RS05140","SYNPCC7942_RS10390","SYNPCC7942_RS10115","SYNPCC7942_RS02720","SYNPCC7942_RS10385","SYNPCC7942_RS10395","SYNPCC7942_RS11730","SYNPCC7942_RS10380","SYNPCC7942_RS09705","SYNPCC7942_RS12670","SYNPCC7942_RS00310","SYNPCC7942_RS05555","SYNPCC7942_RS11905","SYNPCC7942_RS04780","SYNPCC7942_RS08155","SYNPCC7942_RS06400","SYNPCC7942_RS06405","SYNPCC7942_RS04030","SYNPCC7942_RS09540","SYNPCC7942_RS11900","SYNPCC7942_RS05135","SYNPCC7942_RS02850","SYNPCC7942_RS10460","SYNPCC7942_RS11895","SYNPCC7942_RS04850","SYNPCC7942_RS02195","SYNPCC7942_RS08360","SYNPCC7942_RS00090","SYNPCC7942_RS05575","SYNPCC7942_RS13305","SYNPCC7942_RS04925","SYNPCC7942_RS02260","SYNPCC7942_RS09055","SYNPCC7942_RS01045","SYNPCC7942_RS11585","SYNPCC7942_RS10835","SYNPCC7942_RS01335","SYNPCC7942_RS04020","SYNPCC7942_RS12715","SYNPCC7942_RS12990","SYNPCC7942_RS00495","SYNPCC7942_RS12985","SYNPCC7942_RS03035","SYNPCC7942_RS08000","SYNPCC7942_RS01420","SYNPCC7942_RS01630","SYNPCC7942_RS08945","SYNPCC7942_RS12785","SYNPCC7942_RS12930","SYNPCC7942_RS04920","SYNPCC7942_RS05145","SYNPCC7942_RS04760","SYNPCC7942_RS02040","SYNPCC7942_RS07095","SYNPCC7942_RS05250","SYNPCC7942_RS06300","SYNPCC7942_RS10540","Synpcc7942_2454","SYNPCC7942_RS07445","SYNPCC7942_RS01345","SYNPCC7942_RS11670","SYNPCC7942_RS00860","SYNPCC7942_RS04605","SYNPCC7942_RS01465","SYNPCC7942_RS04440","SYNPCC7942_RS04785","SYNPCC7942_RS10295","SYNPCC7942_RS09185","SYNPCC7942_RS01270","SYNPCC7942_RS01880","SYNPCC7942_RS03290","SYNPCC7942_RS01600","SYNPCC7942_RS07835","SYNPCC7942_RS09780","SYNPCC7942_RS09580","SYNPCC7942_RS05570","SYNPCC7942_RS07325","SYNPCC7942_RS07735","SYNPCC7942_RS06990","SYNPCC7942_RS11395","SYNPCC7942_RS03505","SYNPCC7942_RS00195","SYNPCC7942_RS12160","SYNPCC7942_RS01040","SYNPCC7942_RS12520","SYNPCC7942_RS07645","SYNPCC7942_RS09425","SYNPCC7942_RS09440","SYNPCC7942_RS05420","SYNPCC7942_RS04215","SYNPCC7942_RS02485","SYNPCC7942_RS02475","SYNPCC7942_RS11675","SYNPCC7942_RS04655","SYNPCC7942_RS06115","SYNPCC7942_RS06130","SYNPCC7942_RS09965","SYNPCC7942_RS05325","SYNPCC7942_RS11065","SYNPCC7942_RS10595","SYNPCC7942_RS09600","SYNPCC7942_RS09605","SYNPCC7942_RS04820","SYNPCC7942_RS11385","SYNPCC7942_RS11510","SYNPCC7942_RS08865","SYNPCC7942_RS07180","SYNPCC7942_RS09810","SYNPCC7942_RS02255","SYNPCC7942_RS02020","SYNPCC7942_RS02940","SYNPCC7942_RS02570","SYNPCC7942_RS00470","SYNPCC7942_RS06100","SYNPCC7942_RS12945","SYNPCC7942_RS12135","SYNPCC7942_RS09625","SYNPCC7942_RS06385","SYNPCC7942_RS00965","SYNPCC7942_RS07730","SYNPCC7942_RS03380","SYNPCC7942_RS06870","SYNPCC7942_RS06880","SYNPCC7942_RS08870","SYNPCC7942_RS08285","SYNPCC7942_RS09385","SYNPCC7942_RS12690","SYNPCC7942_RS07455","SYNPCC7942_RS03125","SYNPCC7942_RS10435","SYNPCC7942_RS10600","SYNPCC7942_RS10605","Synpcc7942_0034","SYNPCC7942_RS07440","SYNPCC7942_RS00360","SYNPCC7942_RS11870","SYNPCC7942_RS10050","SYNPCC7942_RS09370","SYNPCC7942_RS12995","SYNPCC7942_RS01605","SYNPCC7942_RS02320","SYNPCC7942_RS07240","SYNPCC7942_RS13830","SYNPCC7942_RS06735","SYNPCC7942_RS10055","SYNPCC7942_RS13085","SYNPCC7942_RS12070","SYNPCC7942_RS13075","SYNPCC7942_RS10020","SYNPCC7942_RS01245","SYNPCC7942_RS06730","SYNPCC7942_RS05115","SYNPCC7942_RS06055","SYNPCC7942_RS06865","SYNPCC7942_RS10005","SYNPCC7942_RS10025","SYNPCC7942_RS08205","SYNPCC7942_RS06050","SYNPCC7942_RS06740","SYNPCC7942_RS13080","SYNPCC7942_RS10185","SYNPCC7942_RS02045","SYNPCC7942_RS09670","SYNPCC7942_RS06045","SYNPCC7942_RS03140","SYNPCC7942_RS04025","SYNPCC7942_RS11345","SYNPCC7942_RS12805","SYNPCC7942_RS01415","SYNPCC7942_RS13045","SYNPCC7942_RS10060","SYNPCC7942_RS12100","SYNPCC7942_RS02935","SYNPCC7942_RS07385","SYNPCC7942_RS07330","SYNPCC7942_RS07360","SYNPCC7942_RS12365","SYNPCC7942_RS01575","SYNPCC7942_RS00705","Synpcc7942_0413","SYNPCC7942_RS07690","SYNPCC7942_RS01580","SYNPCC7942_RS09375","SYNPCC7942_RS06950","SYNPCC7942_RS06875","SYNPCC7942_RS01180","SYNPCC7942_RS05290","SYNPCC7942_RS07540","SYNPCC7942_RS13375","SYNPCC7942_RS13245","SYNPCC7942_RS03100","SYNPCC7942_RS02245","SYNPCC7942_RS01005","SYNPCC7942_RS00515","SYNPCC7942_RS08860","SYNPCC7942_RS04960","SYNPCC7942_RS00880","SYNPCC7942_RS09635","SYNPCC7942_RS01890","SYNPCC7942_RS10895","SYNPCC7942_RS07415","SYNPCC7942_RS05720","SYNPCC7942_RS09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Reactions","summary":"To be useful a metabolic model should consist at least of a few reactions.\nThis test simply checks if there are more than zero reactions.\n\nImplementation:\nCheck if the cobra.Model object has non-empty \"reactions\"\nattribute, this list is populated from the list of sbml:listOfReactions\nwhich should contain at least one sbml:reaction.","message":"1015 reactions are defined in the model.","data":["EX_gln__L_e","EX_hco3_e","EX_mn2_e","EX_arg__L_e","ADPT","O2tcx","AOXPBDC","DNTPPA","CBMD","BIOMASS_PIGMENTS","H2Otu_syn","DTMPK","BIOMASS__1","ORNTA","ATPM","ACOATA","5DOAN","3HAD160","RNDR3","Htex","G5SD","HISTDa","TRPS3","DMBZIDS2","HSTPT","ZCAROTDH2","ORNDC","GND","CMPA_1","U23GAAT2","HOXGfx","PGK","IMPD","LPOR","CHRPL","GCALDDy","MSBENZMT","DESAT18a","FUM","PHYFXOR","TMPPP_1","VPAMTr","RNDR1","TALA","GLYCL","ACONT","NDPK7","GTPCI","AIRC2","IGPS","MTAP","HEMEAS_1","DHORD3um","MTHFC","HBZNPT","GCATENEC","COCHL_1","HSDy","TRPS1","HISTDb","UPPDC1","GARFT","H4THDPR","UDPG4E","GLCS3","AICART","ASPTA","GLYOX","PRAGSr","SQD1","ACKr","UDCPDPS","GK1","SHKK","OXADC","G1PACT","3HAD60","PGI","KAS14","OHPBAT","PQH2tum","O2tu","O2tpp","H2Otex","SK_for_c","EX_mg2_e","3HAD80","3OAR160","NMNS","PPK","GALUi","PHYTES2_1","IGPDH","OMPDC","DCTPD","GLUSfx","NADS2","GLUTRR","G1PTT","UAMAGS","SPS","ADCL","CYTK1","DAPDC","PSIum","R05219","Cobalt2abcppI","PFK_3","THRS","NAMNPP","FOLD3","P5CR","MEHLER_1","ICHORS","3OAS140","PPK2","IPDPS_syn","GLYDHDA","SBP","H4THDPS","EAR60y","ZNabcpp","UAPGR","DHAD1","IPPS","ANS","SUCBZL","ADSL1r","NNATr","PERD","PPBNGS","ADOCBLS","LTHRK","PPS","APRAUR","PDS2_1","O2tex","ALAALAr","ADCPS2","GF6PTA","DNMPPA","PGMT","G5SADs","GLCP2_1","AGDI_1","LPADSS2","GLYCK","DPR","EX_ptrc_e","EAR120y","MAN1PT","NMNAT","TKT2","PSP_L","HEX7","PPNCL2","CHORS","CYTBD4cm","PPNCL3","CS","PPCDC","LDH_D","HPYRRy","ADMDC","PRE3BS","PPPGO2_1","BIOMASS_DNA","DMATT","DNAMTn2r","G3PD2","BIOMASS_CELL_WALL","PHYTES","RB15BPtcx","MI3PP","MOHMT","GLXO3r","FBA","RZ5PP","PROAKGOX1","ASAD","CYSS_2","LYCOPC","ACOTA","3HAD180","FTHFD","ALDD2y","3OAS80","PSCVT","CBPS","NTPP8","MEPCT","PDX5POi","DHAD2","DHFS","PGCD","SPMDabcpp","NTD6","NNDMBRT","PRATPP","ASNN","SERAT","PRAIS","PRAMPC","AMPMS3","G1PCTYT","ACBIPGT","SEPHCHCS","NMNDA","CA2abcpp","ORNTAC","SUCBZS","UHGADA2","DHNANT","ASPO6","HGYDAS","GGDPR","ASP1DC","PPNDH","ASPK","DXPS","ME2","3PGtcx","DDPGA","PAPSR","SADT","BIOMASS_COFACTORS","DPCOAK","NH4tpp","DM_h2_c","PC11M","DPOR","ARGSL","HSK","MTHFD","PMDPHT","ARGabcpp","3HAD140","ARGOXRum","DAPE","BCAROHX2","HPPK","PANTS","AHCi","G6PDH2r","ALAD_L","GTPCII","GLCBRAN3","DB4PS","DXPRIi","FBA3","RBFSa","GLUTRS","MPOMMM","METAT","EAR160y","DHORTS","PDX5PS2","KARI_23dhmp_1","ARGDC","GAPDi_nadp","NTD7","AIRC3","UMPK","ASPOb","RBFSb_1","SUCDum","FBP","CITCIb","MNabc_1","TMPK","AGPR","IPMD","CDPMEK","DVOCHR_1","H2CO3_NAt_syn","HEMEOS","PMANM","RPE","MPOMT_1","CPPPGO2","PC17M_1","UAMAS","GLUCYS","NDHPQRum","CYNL","DCTPD2","CYOOum","BPNT2","METS_1","PRUK","FNOR_1","GART","IPPMIb","DMTPHT","PC6YM_1","PGL","DDPA","ASPCT","HSERTA","OMCDC","CYRDAAT","MECDPDHf","Htcx","H2Otpp","HISTP","MTHFR3_1","EX_ca2_e","3HAD40_2","ZCAROTDH1","CYRDAR","BIOMASS_MEM_LIPIDS","HCO3tcx","GLYALDDy","IMPC","BIOMASS_PROTEIN","LDAPAT","EX_nh4_e","3OAR40_2","RNDR2","GRTT","NPDPS","3OAS100","ADSL2r","MAN6PI","HPROb","3OAS120","NTPP2","EAR180y","DHQTi","3OAS60","EAR40y","MG2uabcpp","KARA1","TKT1","PTRCabcpp","IPDDI","PKETF","ACODA","ENO","NDHPQRcm","NI2uabcpp","Kabcpp","TDPDRR","UAGCVT","TDPGDH","PRASCSi","PRFGS","MG2tex","GLU5K","TRDR","GLUPRT","PSERT","PC8XM","GMPS2","RBFK","NTRIRfx","UPP3MT","ACS","DHNCOAS","MCOATA","GTHPi","ARGSS","PKETX","PMPK","HMBS","PTPATi","PGLYCP","HTHRPDH","UAGAAT2","SPTc","GTHOr","TDPDRE","SHK3Dr","ORPT","PRPPS","CITMS","BCT1_syn","SPODM","TRDRf","AMPTASECG","SPRMS","PGAMT","NNDPR","ADSK","MECDPS","FCLT","SHCHCS3","PPA","ADCYRS","ATPPRT","CUabcpp","DHQS","GTHRDH_syn","ANPRT","PC6AR_1","ADK1","PRAIi","TRSARyr","CYNTtabcpp","RBPCcx","UPP3S","DHNPA_1","MOBDabcpp","NADK","BIOMASS_RNA","NADTRHD","PGM","FE3abcpp","DM_dialurate_c","CO2tex","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","EX_fe2_e","PQH2tcm","2PGLYCtcx","PDS1_1","EX_cu2_e","FRTT","3OAS180","EAR80y","DM_5drib_c","SK_amylose_c","EAR140y","EX_k_e","ACGS","CYTBD4um","DHPPDA","DHFR","BCAROHX","SK_14glucan_c","SK_glycogen_c","EX_h2o_e","EX_o2_e","EX_co2_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","EX_cobalt2_e","EX_no3_e","EX_zn2_e","EX_fe3_e","EX_so4_e","AFAT","EX_spmd_e","EX_mobd_e","DADK","G1SAT","EX_ni2_e","UAAGDS","HEX1","URIDK2r","CHPHYS","EX_na1_e","PIuabcpp","ARGDHpp","PHETA1","PFK","DMPPS_syn","ANS2","3OAS160","ACHBSb","PC20M","ADSS","THRPDC","MPOMOR_1","EX_cynt_e","IPPMIa","SPMS","EX_h_e","BPNT","ICDHyr","TMDS3","GLYOX_1","MTRI","CTPS2","FE3tex","GTHS","AHSERL2_1","PEPC","CHORM","NTRARf2","FE2tex","G6PDA","MPML","Nat_Kpp","PDH","TPI","E4PD","GAPD","CPPPGO","PRMICI","CAT","GLUR","OCBT","NI2tex","GLGC","PYK","CA2t2pp","ALAR","SULR_2","ADCS","UGMDDS","GLCDBRAN3","IG3PS","RPI","NAt3pp","MNtex","GLYCLTDx","FMNRy_1","GHMT2r","COBALT2tex","PGPP_OLE_PALM","CU2tex","MEOHtrpp","MEOHtex","H2Otcx","Zn2tex","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","DM_amob_c","ADNK1","OPMEACPD","OPMEACPR","EX_photon530_e","EX_photon550_e","SPP","SPMDtex","AGPAT160","EX_photon570_e","EX_photon590_e","EX_photon610_e","AGPATACP_HDE_PALM","LEUtex","BTS6","QUERT","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","HCO3tex","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","GLNtex","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","CYNTtex","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","ARGtex","GLUDGS_HDE_HDE","TYRTRS","DAGK160","MOBDtex","DAGK_HDE_PALM","DAGK161","NH4tex","SQDGS_PALM_PALM","SO4tex","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","PTRCtex","DGDGS_HDE_HDE","NO3tex","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","NAtex","PROTRS","GLYTRS","CYSTRS","CA2tex","ARGTRS","Ktex","TRPTRS","HISTRS","CO2tpp","PHETRS","EX_pi_e","ASNTRS","ASPTRS","UDPGLDC","PItex","AGTi","DBTS","THRTRS","LEUTRS","ILETRS","CHLADMT_1","LYSTRS","AOXSr2","AMAOTr","LIPOS2","ALATRS","TRNFE","VALTRS","FMETTRS","BACCL","BTNPL2","LIPAMPL_1","LIPOCT","LIPATPT_1","ZXANHX","PHOA410um","PHOA430um","CPH4S","OGMEACPR","CDGS","PHOA450um","PHOA470um","PHOA490um","CCGS","CDGR","PHOA510um","PHOA530um","PLYCOI","PHOA550um","SAMTRI","EPXQR","UPPRT","PHOA570um","PHOA590um","PHOA610um","ZCARDS","PHOA630um","PHOA650um","PHOA670um","UDPGD","GMAND","GFUCS","PHOA690um","NADDP","DM_pho_loss_c","ETCHLAS","ETBCARO","COLIPAabcex","MLDCP1App","CDPGLC46DH","AACPS6","ALDR18","ALDDC17","ALCD19","THZT","MLDCP1Bpp","PHYPQOX","MLDCP2App","MLDCP2Bpp","LALGP","AGM4Pt2pp","AGMt2pp","CXANHX","OGMEACPS","A5PISO","KDOPS","KDOPP","EX_meoh_e","NO2tex","KDOCT2","EGMEACPR","DXYTST","UAG2E","OANTS","ACGAMT","Htabcpp","ETAPCPSII","STCHLPSIum","DEXZEAX","PFOR","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","UAGPT3","GLYCOX1","UM4PL","UM3PL","PAPPT3","OANTIabcpp","OANTILpp","MDDCP1pp","MDDCP2pp","STACPSI","UDCPDP","MLTGY1pp","ETCPC","GLYCOX2","NO2tabcpp","MLTGY2pp","MLTGY3pp","MLTGY4pp","AGM4PA","FALGTHLs","CLtex","EX_cl_e","AM3PA","AM4PA","SK_fum_c","MALCOAMT","DM_succ_c","AGM3PApp","AGM4PApp","UM4PCP","SK_akg_c","MDRPD","NGAM_D1um","PSICRum","AM4PCP","4PCP","AGM4PCP","AGMH","PSIICRum","DM_ac_c","AGM3PH","DM_lac__D_c","ENOPH","NGAM","QULNS","AGM4PH","LADGMDH","ILETA","ALAGLUE","CELLSYN","ALAALAabcpp","LEUTA","ARD","VALTA","NDPK3","NDPK6","NDPK1","4PEPTabcpp","ALAALAD","ADPGLC","NDPK8","UNK3","NDPK5","DALAabcpp","NDPK4","ZISO","NDPK2","3OAR180","3OAR140","PAPA160","PHEOASE","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","ACGK","MCTP2App","MCTP1App","MCTP1Bpp","LEUabcpp","ACLSa","SULabcpp","PAPA_OLE_PALM","TYRTA","ACLSb","PHEOX_1","OPMEACPS","EAR100y","EHGLAT","KAS15","FALDH2","PHYTK","NDH_1_4_um_copy2","KARI_1","3HAD120","OGMEACPD","ACCOAC","ASPO5","PTHPS","CITCIa","DAGK_OLE_HDE","DAGK_OLE_PALM","3HAD100","PNTK","3OAR120","3OAR60","3OAR100","3OAR80","ALCD1","NDH_1_1_um_copy1","NDH_1_4_um_copy1","PCHLDA430","SFGTHi","PCHLDA650","GGCLUT2","SPR","OPAH","ACGAMK","AMANAPEr","AGDC","ANHMK","RNDR4","TRPS2","PSICSum","NAD_H2","PPND","CBFCum","ACM6PH","SUCR","CLt3_1pp","Ktu","THBTGT","FDH6","PCXHtpp","THISAT","PSIIum","ATPSum","CYSDES","NO3abcpp","GLNabcpp","GLNS","MDDEP1pp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","ASNS1","MDDCP3pp","MDDCP4pp","MDDCP5pp","MDDEP2pp","MDDEP3pp","MDDEP4pp","MNHNAtpp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX_glyc_e","EX_fuc__L_e","EX_glcur_e","EX_glcn_e","EX_glyc3p_e","EX_xyl__D_e","EX_lac__L_e","EX_g6p_e","EX_malt_e","EX_melib_e","EX_thymd_e","EX_galctn__D_e","EX_rib__D_e","EX_rmn_e","EX_fru_e","EX_ac_e","EX_glc__D_e","EX_asn__L_e","EX_sucr_e","EX_uri_e","EX_12ppd__S_e","EX_akg_e","EX_lcts_e","EX_malttr_e","EX_dad_2_e","EX_adn_e","EX_g1p_e","EX_f6p_e","EX_ins_e","EX_cit_e","EX_inost_e","EX_fum_e","EX_ppa_e","EX_galct__D_e","EX_glyclt_e","EX_mal__D_e","EX_mal__L_e","EX_ser__L_e","EX_thr__L_e","EX_ala__L_e","EX_acac_e","EX_acmana_e","EX_galur_e","EX_peamn_e","EX_etha_e","EX_tym_e","EX_lyx__L_e","EX_pyr_e","EX_galctn__L_e","EX_acnam_e","EX_all__D_e","EX_4abut_e","EX_but_e","EX_dca_e","EX_5dglcn_e","EX_hxa_e","EX_tartr__L_e","EX_lys__L_e","EX_met__L_e","EX_gly_e","EX_his__L_e","EX_hom__L_e","EX_ile__L_e","EX_orn_e","EX_phe__L_e","EX_val__L_e","EX_dha_e","EX_cys__L_e","EX_no2_e","EX_urea_e","EX_trp__L_e","EX_tyr__L_e","EX_agm_e","EX_acgal_e","EX_gam_e","EX_ura_e","EX_ade_e","EX_cytd_e","EX_csn_e","EX_gua_e","EX_gsn_e","EX_thym_e","EX_xan_e","EX_xtsn_e","EX_alltn_e","EX_23camp_e","EX_3amp_e","EX_gmp_e","EX_23cgmp_e","EX_3gmp_e","EX_cmp_e","EX_23ccmp_e","EX_gam6p_e","EX_3cmp_e","EX_ump_e","EX_23cump_e","EX_man6p_e","EX_pser__L_e","EX_thrp_e","EX_3ump_e","EX_tyrp_e","EX_minohp_e","SUCRt2","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","MDH","FNOR","PC6YM","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE10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Metabolites","summary":"To be useful a metabolic model should consist at least of a few\nmetabolites that are converted by reactions.\nThis test simply checks if there are more than zero metabolites.\n\nImplementation:\nCheck if the cobra.Model object has non-empty\n\"metabolites\" attribute, this list is populated from the list of\nsbml:listOfSpecies which should contain at least one sbml:species.","message":"924 metabolites are defined in the 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Since it may be\ndifficult to obtain formulas for certain metabolites this test serves as a\nmere report. Models can still be stoichiometrically consistent even\nwhen chemical formulas are not defined for each metabolite.\n\nImplementation:\nCheck if each cobra.Metabolite has a non-empty \"formula\"\nattribute. This attribute is set by the parser if there is an\nfbc:chemicalFormula attribute for the corresponding species in the\nSBML.","message":"There are a total of 140         metabolites (15.15%) without a\nformula: bm_pigm_c, bm_pro_c, bm_cofactors_c, bm_carbs_c, bm_cw_c, ...","data":["bm_pigm_c","bm_pro_c","bm_cofactors_c","bm_carbs_c","bm_cw_c","bm_rna_c","bm_memlip_c","bm_dna_c","icolipacy_c","icolipacy_p","oanticy_c","oanticy_p","colipacy_p","colipacy_e","tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c"],"format_type":"count","metric":0.15151515151515152},"test_metabolites_charge_presence":{"duration":0.00021949199998516633,"result":"passed","title":"Metabolites without Charge","summary":"To be able to ensure that reactions are charge-balanced, all model\nmetabolites ought to be provided with a charge. Since it may be\ndifficult to obtain charges for certain metabolites this test serves as a\nmere report. Models can still be stoichiometrically consistent even\nwhen charge information is not defined for each metabolite.\n\nImplementation:\nCheck if each cobra.Metabolite has a non-empty \"charge\"\nattribute. This attribute is set by the parser if there is an\nfbc:charge attribute for the corresponding species in the\nSBML.","message":"There are a total of 0         metabolites (0.00%) without a charge:","data":[],"format_type":"count","metric":0.0},"test_gene_protein_reaction_rule_presence":{"duration":0.0027892420000057427,"result":"failed","title":"Reactions without GPR","summary":"Gene-Protein-Reaction rules express which gene has what function.\nThe presence of this annotation is important to justify the existence\nof reactions in the model, and is required to conduct in silico gene\ndeletion studies. However, reactions without GPR may also be valid:\nSpontaneous reactions, or known reactions with yet undiscovered genes\nlikely lack GPR.\n\nImplementation:\nCheck if each cobra.Reaction has a non-empty\n\"gene_reaction_rule\" attribute, which is set by the parser if there is an\nfbc:geneProductAssociation defined for the corresponding reaction in the\nSBML.","message":"There are a total of 146 reactions (14.38%) without GPR:\nGLXO3r, RZ5PP, PHOA550um, CSND, PItex, ...","data":["GLXO3r","RZ5PP","PHOA550um","CSND","PItex","PHOA610um","FACOAL100i","MOCOS","DPGM","BIOMASS_PROTEIN","MOADSUx","NO2tex","FACOAE180","HCO3tex","PHOA410um","ADNK1","DRPA","MOBDtex","FACOAL140i","ETAPCPSII","O2tex","G1Dx","BIOMASS_CELL_WALL","FACOAL160i","O2tcx","GUACYC","MPTAT","LEUtex","PHOA570um","3PGtcx","H2Otcx","HCO3tcx","FACOAL161i","RDXRr","CBMD","NH4tex","BIOMASS_RNA","MPTSS","PHOA630um","CU2tex","DNTPPA","PHOA590um","DNMPPA","FA100ACPHi","CHLADMT_1","FACOAL180i","Htcx","CPMPS","MNtex","MLDCP2App","5DOAN","FA120ACPHi","CA2tex","Ktex","FACOAL181i","STCHLPSIum","GTPC","PQH2tcm","FA140ACPHi","AOXPBDC","BIOMASS_MEM_LIPIDS","PHOA670um","MLDCP1Bpp","MDH","FACOAL80i","SPMDtex","H2Otex","BIOMASS_COFACTORS","FA160ACPHi","PHOA650um","PHOA490um","NO3tex","GLCP4","FA161ACPHi","FE3tex","Zn2tex","PSIICRum","CLtex","Htabcpp","O2tu","GLCP3","GLNtex","O2tpp","FA180ACPHi","BIOMASS_PIGMENTS","NI2tex","PHOA450um","G5SADs","DEXZEAX","FA181ACPHi","PTRCtex","NGAM","CYSTL","HISTP","CO2tpp","MEOHtex","PHOA470um","AGM4Pt2pp","PHOA690um","FA80ACPHi","CYRDAR","FACOAE80","FALGTHLs","USHD2","ATPM","H2Otu_syn","FACOAE100","H2Otpp","PQH2tum","AGMt2pp","TRNFE","FACOAE120","RB15BPtcx","NAtex","PHOA530um","MLDCP1App","COBALT2tex","NGAM_D1um","FACOAE140","MEOHtrpp","CYNTtex","OMCDC","FACOAE160","Htex","BIOMASS_CARB","FE2tex","PHOA510um","MLDCP2Bpp","COLIPAabcex","PHOA430um","CO2tex","ETBCARO","ETCHLAS","FACOAE161","DRBK","APRAUR","FACOAL120i","PSICRum","AMAA","SO4tex","MPTS","2PGLYCtcx","PGPP_OLE_PALM","BIOMASS__1","ARGtex","FACOAE181"],"format_type":"count","metric":0.1438423645320197},"test_ngam_presence":{"duration":0.14336537600001975,"result":"passed","title":"Non-Growth Associated Maintenance Reaction","summary":"The Non-Growth Associated Maintenance reaction (NGAM) is an\nATP-hydrolysis reaction added to metabolic models to represent energy\nexpenses that the cell invests in continuous processes independent of\nthe growth rate. Memote tries to infer this reaction from a list of\nbuzzwords, and the stoichiometry and components of a simple ATP-hydrolysis\nreaction.\n\nImplementation:\nFrom the list of all reactions that convert ATP to ADP select the reactions\nthat match the irreversible reaction \"ATP + H2O -> ADP + HO4P + H+\",\nwhose metabolites are situated within the main model compartment.\nThe main model compartment is assumed to be the cytosol, yet, if that\ncannot be identified, it is assumed to be the compartment with the most\nmetabolites. The resulting list of reactions is then filtered further by\nattempting to match the reaction name with any of the following buzzwords\n('maintenance', 'atpm', 'requirement', 'ngam', 'non-growth', 'associated').\nIf this is possible only the filtered reactions are returned, if not the\nlist is returned as is.","message":"A total of 1 NGAM reactions could be identified:         ATPM","data":["ATPM"],"format_type":"count","metric":0.0},"test_metabolic_coverage":{"duration":0.00016064099997947778,"result":"passed","title":"Metabolic Coverage","summary":"The degree of metabolic coverage indicates the modeling detail of a\ngiven reconstruction calculated by dividing the total amount of\nreactions by the amount of genes. Models with a 'high level of modeling\ndetail have ratios >1, and models with a low level of detail have\nratios <1. This difference arises as models with basic or intermediate\nlevels of detail are assumed to include many reactions in which several\ngene products and their enzymatic transformations are ‘lumped’.\n\nImplementation:\nDivides the amount reactions by the amount of genes. Raises an error\nif the model does not contain either reactions or genes.","message":"The degree of metabolic coverage is 1.2.","data":[1015,882],"format_type":"percent","metric":1.1507936507936507},"test_compartments_presence":{"duration":0.00045395099999723243,"result":"passed","title":"Total Compartments","summary":"While simplified metabolic models may be perfectly viable, generally\nacross the tree of life organisms contain at least one distinct\ncompartment: the cytosol or cytoplasm. In the case of prokaryotes there is\nusually a periplasm, and eurkaryotes are more complex. In addition to the\ninternal compartment, a metabolic model also reflects the extracellular\nenvironment i.e. the medium/ metabolic context in which the modelled cells\ngrow. Hence, in total, at least two compartments can be expected from a\nmetabolic model.\n\nImplementation:\nCheck if the cobra.Model object has a non-empty \"compartments\"\nattribute, this list is populated from the list of sbml:listOfCompartments\nwhich should contain at least two sbml:compartment elements.","message":"A total of 7 compartments are defined in the model: c, cx, u, um, cm,\n...","data":["c","cx","u","um","cm","p","e"],"format_type":"count","metric":0.0},"test_protein_complex_presence":{"duration":0.016646448000017244,"result":"passed","title":"Enzyme Complexes","summary":"Based on the gene-protein-reaction (GPR) rules, it is possible to infer\nwhether a reaction is catalyzed by a single gene product, isozymes or by a\nheteromeric protein complex. This test checks that at least one\nsuch heteromeric protein complex is defined in any GPR of the model. For\nS. cerevisiae it could be shown that \"essential proteins tend to [cluster]\ntogether in essential complexes\"\n(https://doi.org/10.1074%2Fmcp.M800490-MCP200).\n\nThis might also be a relevant metric for other organisms.\n\nImplementation:\nIdentify GPRs which contain at least one logical AND that combines two\ndifferent gene products.","message":"A total of 93 reactions are catalyzed by complexes defined\nthrough GPR rules in the model.","data":["TRPS3","ZCAROTDH2","GLYCL","COCHL_1","TRPS1","PSIum","Cobalt2abcppI","MEHLER_1","ZNabcpp","ANS","LPADSS2","CYTBD4cm","BIOMASS_DNA","CBPS","DHNANT","DPOR","ARGabcpp","SUCDum","CITCIb","MNabc_1","CYOOum","IPPMIb","ASPCT","Kabcpp","PRFGS","BCT1_syn","TRDRf","ATPPRT","CYNTtabcpp","RBPCcx","MOBDabcpp","NADTRHD","FE3abcpp","NPHBDC","CYTBD4um","PIuabcpp","ANS2","ACHBSb","IPPMIa","MPML","Nat_Kpp","PDH","GLCDBRAN3","IG3PS","GLYCLTDx","BTS6","G3PAT160","G3PAT161","G3PAT1819Z_1","GLNTRS","GLYTRS","PHETRS","LIPOS2","OANTS","ICLIPAS","MOAT_1","MPTG","MPTG2","OANTIabcpp","OANTILpp","ETCPC","NO2tabcpp","CELLSYN","ALAALAabcpp","4PEPTabcpp","DALAabcpp","LEUabcpp","ACLSa","SULabcpp","ACLSb","NDH_1_4_um_copy2","ACCOAC","CITCIa","NDH_1_1_um_copy1","NDH_1_4_um_copy1","TRPS2","PSICSum","NAD_H2","CBFCum","CLt3_1pp","THISAT","PSIIum","ATPSum","CYSDES","NO3abcpp","GLNabcpp","THII","SHS1","PSIICSum","NDH_1_1_um_copy2","ASNS1","MNHNAtpp","FNOR"],"format_type":"count","metric":0.0916256157635468},"test_find_pure_metabolic_reactions":{"duration":0.006283237999980429,"result":"passed","title":"Purely Metabolic Reactions","summary":"If a reaction is neither a transport reaction, a biomass reaction nor a\nboundary reaction, it is counted as a purely metabolic reaction. This test\nrequires the presence of metabolite formula to be able to identify\ntransport reactions. This test is passed when the model contains at least\none purely metabolic reaction i.e. a conversion of one metabolite into\nanother.\n\nImplementation:\nFrom the list of all reactions, those that are boundary, transport and\nbiomass reactions are removed and the remainder assumed to be pure\nmetabolic reactions. Boundary reactions are identified using the attribute\ncobra.Model.boundary. Please read the description of \"Transport Reactions\"\nand \"Biomass Reaction Identified\" to learn how they are identified.","message":"A total of 706 (69.56%) purely metabolic reactions are defined in\nthe model, this excludes transporters, exchanges, or pseudo-reactions:\nUM4PL, BPNT2, G1PTT, AGPATACP_OLE_HDE, HISTDa, ...","data":["UM4PL","BPNT2","G1PTT","AGPATACP_OLE_HDE","HISTDa","HPROb","PC17M_1","NADS2","NDPK2","G1PACT","3OAR180","ASP1DC","G3PAT161","KARA1","ZISO","ARGTRS","UAGPT3","GLUTRR","TYRTRS","TKT1","CYSTRS","3HAD60","GLUDGE_OLE_PALM","MAN6PI","SPTc","HISTRS","4PCP","UAGAAT2","AGM3PH","3OAR140","PGI","AGM4PCP","KAS14","PAPA160","P5CR","SERTRS","UM3PL","AGMH","PHEOASE","RNDR3","DBTS","PAPPT3","PSIICRum","PAPA_HDE_PALM","NTPP2","GLUDGE_HDE_PALM","UAMAS","ICHORS","ADCL","PAPA161","TDPDRE","AGPAT161","SPS","GTHOr","UAMAGS","OHPBAT","PAPA_OLE_HDE","GLUDGS_HDE_PALM","OANTILpp","PRUK","ENOPH","AGM4PH","AGPATACP_OLE_PALM","SHK3Dr","ACGK","MLTGY1pp","3OAS120","MEHLER_1","PDS2_1","PHETRS","MDDCP1pp","ASPTRS","MCTP2App","QULNS","GLUDGS_OLE_HDE","ASNTRS","MCTP1App","3HAD80","MDDCP2pp","LADGMDH","MCTP1Bpp","UDPGLDC","GLUDGS_OLE_PALM","PHEOX_1","G5SD","DHNCOAT","GND","STACPSI","ILETA","GALUi","FNOR_1","PRPPS","PKETF","ORPT","ALAGLUE","UDCPDP","AOXSr2","PPK2","GLUDGS_HDE_HDE","CELLSYN","3OAS140","ACLSa","CYTK1","DAGK161","AGTi","NADTRHD","THRS","METS_1","DAGK160","CYNL","THRTRS","ETCPC","3OAR160","EAR180y","GLYCOX2","VALTA","CITMS","MLTGY2pp","LEUTA","DMBZIDS2","DAPDC","IPDPS_syn","TRPS3","ADCPS2","ADPT","ALAALAr","LEUTRS","PPK","DAGK_HDE_PALM","VALTRS","ILETRS","NMNS","MLTGY4pp","CBMD","PAPA_OLE_PALM","ACOATA","DNTPPA","CHLADMT_1","MLTGY3pp","GLYDHDA","IPPMIb","ARD","NPDPS","ENO","5DOAN","SQDGS_PALM_PALM","CMPA_1","PGPS_OLE_PALM","LYSTRS","IPDDI","ACLSb","R05219","EAR100y","AOXPBDC","FMETTRS","3HAD160","H4THDPS","OPMEACPS","ORNDC","OGMEACPR","SQDGS_HDE_PALM","HSTPT","SBP","U23GAAT2","NDPK3","DCTPD","AMAOTr","DHQTi","NDPK6","3OAS60","SPODM","DGDGS_HDE_PALM","NDPK1","AMPTASECG","ZCAROTDH2","NDPK8","LIPOS2","IGPDH","TYRTA","DCTPD2","EAR40y","PHYTES2_1","AGM4PA","ALATRS","PFK_3","ALAALAD","GART","FALGTHLs","DGDGS_HDE_HDE","ATPM","DGDGS_OLE_PALM","NDH_1_4_um_copy2","OMPDC","NDPK5","TRNFE","DGDGS_OLE_HDE","NAMNPP","METTRS","FOLD3","EAR60y","NNDPR","ORNTA","TRDRf","EHGLAT","DTMPK","GLYTRS","NDPK4","ADPGLC","ADSL2r","PGAMT","CDPDAGS_OLE_PALM","UM4PCP","KAS15","CPH4S","AM4PCP","3OAS100","PGLYCP","UAPGR","AGM4PApp","FALDH2","TRPTRS","BACCL","AGM3PApp","GLNTRS","ACODA","LIPOCT","PROTRS","MOAT_1","BTNPL2","UNK3","MDRPD","LIPAMPL_1","PHYTK","GLUSfx","DMTPHT","TMDS3","SPRMS","RBPCcx","MOCOS","KARI_1","DPOR","ADCS","MOADSUx","PSCVT","DXPS","PSP_L","3OAR40_2","LIPATPT_1","UGMDDS","ALDR18","OGMEACPD","GLYCL","RBFSa","CBPS","FACOAL140i","BCAROHX","GLCDBRAN3","ZXANHX","ME2","MDDEP4pp","GLUTRS","CHPHYS","NTPP8","ACCOAC","FACOAL160i","ALDDC17","IMPD","MPTAT","MPOMMM","IG3PS","ASPO5","NTRIRfx","FACOAL161i","GLYOX_1","PTHPS","PDX5POi","HOXGfx","DHPPDA","ALCD19","PPNCL2","AHSERL2_1","MPTSS","ACONT","MEPCT","DNMPPA","GARFT","IPPS","RPI","CITCIa","METAT","FACOAL180i","ADSK","GLNS","CPMPS","MLDCP2App","THZT","FACOAL181i","AGDC","CHORS","EAR160y","ARGSS","LALGP","ANHMK","GTPC","MECDPS","PPNCL3","PGK","DESAT16a","MLDCP1Bpp","MDH","FACOAL80i","MDDEP1pp","DHAD2","MTRI","DHAD1","DHORTS","DHFR","SPMS","RNDR4","FNOR","GLCP4","PGL","CTPS2","DHFS","CDGS","DPCOAK","GTPCI","PDX5PS2","RBFK","PC6YM","ANS","FCLT","GLCP3","PGCD","TRPS2","H4THDPR","PC6YM_1","SHCHCS3","KARI_23dhmp_1","PMPK","NDPK7","3HAD120","CYSTL","MTAP","PKETX","GTHS","SUCBZL","UPP3S","PLYCOI","ARGDC","UDPG4E","CCGS","FACOAE80","CXANHX","NAD_H2","NTD6","ICDHyr","GAPDi_nadp","PEPC","EGMEACPR","AIRC2","PRE3BS","SPP","TDPDRR","3HAD100","NNDMBRT","NTD7","MCOATA","DAGK_OLE_HDE","CDGR","FMNRy_1","LPOR","CHORM","OGMEACPS","AGDI_1","ACM6PH","SHKK","PPA","PRFGS","TRDR","IGPS","GLCS3","PRATPP","DAGK_OLE_PALM","PFK","MTHFD","AIRC3","MPML","CDPGLC46DH","KDOCT2","THII","NTRARf2","SHS1","PTPATi","IPPMIa","NNATr","ASNN","A5PISO","GCALDDy","UMPK","ADSL1r","DMPPS_syn","SUCR","ASPOb","MPOMOR_1","CHRPL","GLCP2_1","PPCDC","ARGSL","LYCBC1","DRBK","CS","ASNS1","AMAA","PERD","SERAT","PGPP_OLE_PALM","ATPPRT","UAGDP","AICART","DDPA","ADCYRS","FBA","KDOPS","PNTK","RBFSb_1","KDOPP","MOGDS","GLXO3r","RZ5PP","PRAIS","CSND","AMPMS3","NADK","3OAR120","DHNPA_1","EPXQR","ASPTA","PRASCSi","HSK","HMBS","MPOMC1_1","FACOAL100i","DPGM","PRAMPC","ZCAROTDH1","MSBENZMT","MALCOAMT","ERTHMMOR","3OAR60","MAN1PT","FBP","GRTT","GHMT2r","LPADSS2","SAMTRI","HEMEAS_1","HSERTA","GAPD","PPND","3OAR100","PMDPHT","UPP3MT","PDH","FACOAE180","DAPE","LDH_D","ANS2","GLYOX","GLYCK","ADNK1","UPPRT","PHYFXOR","CITCIb","DRPA","G1PCTYT","3OAR80","FACOAE181","ASAD","BCAROHX2","OPMEACPD","ACBIPGT","DXYTST","ETAPCPSII","G1Dx","ASPCT","ALCD1","3HAD140","TPI","GUACYC","DESAT18a","ADOCBLS","HEX7","PRAGSr","HTHRPDH","UAG2E","PPBNGS","EAR120y","E4PD","PAPSR","NDH_1_1_um_copy1","FDH6","HPYRRy","3OAS160","RDXRr","OPMEACPR","CYRDAAT","GLU5K","PDS1_1","SEPHCHCS","PGM","TDPGDH","PROAKGOX1","CAT","FA100ACPHi","RNDR2","GLYALDDy","TMPK","MECDPDHf","OANTS","PYK","MTHFC","DPR","ACGAMT","ACS","NDH_1_4_um_copy1","NMNDA","FA120ACPHi","ALDD2y","FUM","ADMDC","LYCOPC","CYSDES","DHQS","3OAS180","STCHLPSIum","THBTGT","HCO3E_1_cx","FA140ACPHi","ACKr","ANPRT","CPPPGO","ALAR","SQD1","FA160ACPHi","IPMD","LTHRK","ORNTAC","HPPK","AFAT","UDPGD","HBZNPT","UDCPDPS","G3PD2","GTHRDH_syn","CDPMEK","FRTT","AGPAT160","FA161ACPHi","PSERT","SADT","PC20M","GLUPRT","ACHBSb","SUCBZS","AGPR","CYSS_2","FA180ACPHi","LDAPAT","DHNCOAS","THISAT","PPS","EAR140y","PRMICI","TRPS1","PANTS","GMAND","GGCLUT2","HISTDb","G5SADs","DEXZEAX","GF6PTA","ASPK","ACGAMK","UHGADA2","DADK","FA181ACPHi","GCATENEC","ACOTA","HEX1","HISTP","AGPATACP_HDE_PALM","SPR","DNAMTn2r","DVOCHR_1","G6PDA","AHCi","SULR_2","GFUCS","AMANAPEr","FA80ACPHi","DHNANT","PC8XM","NPHBDC","CYRDAR","EAR80y","USHD2","GLUR","NDH_1_1_um_copy2","BPNT","QUERT","TMPPP_1","FBA3","GLUCYS","PFOR","ACGS","FACOAE100","IMPC","GMPS2","AACPS6","VPAMTr","ASPO6","PRAIi","G6PDH2r","BTS6","ACMAMT","COCHL_1","OCBT","PPPGO2_1","MTHFR3_1","TRSARyr","THRPDC","GLYCOX1","FACOAE120","AM4PA","GGDPR","ALAD_L","AM3PA","3HAD40_2","G1SAT","3OAS80","EPMEACPR","MLDCP1App","MDDCP5pp","NMNAT","3HAD180","HGYDAS","PGMT","DDPGA","ADSS","FTHFD","UAGCVT","PMEACPE","FACOAE140","HEMEOS","ARGDHpp","GLUDGE_OLE_HDE","ADK1","PHETA1","NADDP","OMCDC","MDDCP3pp","MDDEP2pp","MI3PP","GTPCII","RPE","GK1","PC11M","PC6AR_1","HSDy","G3PAT1819Z_1","FACOAE160","DMATT","MOHMT","CPPPGO2","GLGC","MLDCP2Bpp","MDDCP4pp","TKT2","PHYTES","ETBCARO","DXPRIi","PMANM","PPNDH","GLYCLTDx","GLUDGE_HDE_HDE","GTHPi","ICLIPAS","ETCHLAS","G3PAT160","FACOAE161","GLCBRAN3","MPOMT_1","URIDK2r","TALA","OXADC","OPAH","FACOAL120i","UPPDC1","APRAUR","SFGTHi","RNDR1","MDDEP3pp","MPTS","UAAGDS","DB4PS"],"format_type":"count","metric":0.6955665024630542},"test_find_constrained_pure_metabolic_reactions":{"duration":0.002382941000007577,"result":"passed","title":"Purely Metabolic Reactions with Constraints","summary":"If a reaction is neither a transport reaction, a biomass reaction nor a\nboundary reaction, it is counted as a purely metabolic reaction. This test\nrequires the presence of metabolite formula to be able to identify\ntransport reactions. This test simply reports the number of purely\nmetabolic reactions that have fixed constraints and does not have any\nmandatory 'pass' criteria.\n\nImplementation: From the pool of pure metabolic reactions identify\nreactions which are constrained to values other than the model's minimal or\nmaximal possible bounds.","message":"A total of 11 (1.56%) purely metabolic reactions have fixed\nconstraints in the model, this excludes transporters, exchanges, or\npseudo-reactions: -1000.0 <= KARA1 <= 0.0, -1000.0 <= IPPMIb <= 0.0,\n0.0 <= NDH_1_4_um_copy2 <= 0.0, 0.0 <= DPOR <= 0.0, -1000.0 <= IPPMIa\n<= 0.0, ...","data":["-1000.0 <= KARA1 <= 0.0","-1000.0 <= IPPMIb <= 0.0","0.0 <= NDH_1_4_um_copy2 <= 0.0","0.0 <= DPOR <= 0.0","-1000.0 <= IPPMIa <= 0.0","-1000.0 <= ASAD <= 0.0","-1000.0 <= LDAPAT <= 0.0","0.0 <= NDH_1_1_um_copy2 <= 0.0","-1000.0 <= HSDy <= 0.0","0.0 <= CPPPGO2 <= 0.0","-1000.0 <= GLYCLTDx <= 0.0"],"format_type":"count","metric":0.015580736543909348},"test_find_transport_reactions":{"duration":0.00024457899996832566,"result":"passed","title":"Transport Reactions","summary":"Cellular metabolism in any organism usually involves the transport of\nmetabolites across a lipid bi-layer. This test reports how many\nof these reactions, which transports metabolites from one compartment\nto another, are present in the model, as at least one transport reaction\nmust be present for cells to take up nutrients and/or excrete waste.\n\nImplementation:\nA transport reaction is defined as follows:\n1. It contains metabolites from at least 2 compartments and\n2. at least 1 metabolite undergoes no chemical reaction, i.e.,\nthe formula and/or annotation stays the same on both sides of the equation.\n\nA notable exception is transport via PTS, which also contains the following\nrestriction:\n3. The transported metabolite(s) are transported into a compartment through\nthe exchange of a phosphate.\n\nAn example of transport via PTS would be\npep(c) + glucose(e) -> glucose-6-phosphate(c) + pyr(c)\n\nReactions similar to transport via PTS (referred to as \"modified transport\nreactions\") follow a similar pattern:\nA(x) + B-R(y) -> A-R(y) + B(y)\n\nSuch modified transport reactions can be detected, but only when the\nformula is defined for all metabolites in a particular reaction. If this\nis not the case, transport reactions are identified through annotations,\nwhich cannot detect modified transport reactions.","message":"A total of 123 (12.12%) transport reactions are defined in the\nmodel, this excludes purely metabolic reactions, exchanges, or\npseudo-reactions: LEUabcpp, PHOA550um, PHOA610um, PItex, Nat_Kpp, ...","data":["LEUabcpp","PHOA550um","PHOA610um","PItex","Nat_Kpp","Kabcpp","SUCDum","ALAALAabcpp","MNHNAtpp","ATPSum","NO2tex","MPTG","HCO3tex","PHOA410um","CYTBD4cm","PTRCabcpp","MOBDtex","SULabcpp","ARGabcpp","CBFCum","O2tex","Ktu","MPTG2","O2tcx","DHORD3um","NH4tpp","CYNTtabcpp","ARGOXRum","LEUtex","BCT1_syn","PHOA570um","3PGtcx","H2Otcx","MNabc_1","HCO3tcx","NH4tex","PHYPQOX","PSIum","PHOA630um","CU2tex","PHOA590um","MG2uabcpp","Htcx","PSIIum","ZCARDS","MNtex","CA2tex","Ktex","MG2tex","Cobalt2abcppI","PQH2tcm","CA2abcpp","NDHPQRum","PHOA670um","SPMDtex","H2Otex","NAt3pp","NO3abcpp","PHOA650um","PCHLDA650","PHOA490um","NO3tex","PCXHtpp","FE3tex","NO2tabcpp","Zn2tex","CLtex","GLNabcpp","Htabcpp","O2tu","GLNtex","O2tpp","PSIICSum","NI2uabcpp","MOBDabcpp","NI2tex","NDHPQRcm","4PEPTabcpp","PHOA450um","OANTIabcpp","PTRCtex","PSICSum","NGAM","SPMDabcpp","CO2tpp","MEOHtex","PHOA470um","AGM4Pt2pp","PHOA690um","H2Otu_syn","H2Otpp","PQH2tum","AGMt2pp","CLt3_1pp","FE3abcpp","H2CO3_NAt_syn","RB15BPtcx","NAtex","PHOA530um","CUabcpp","COBALT2tex","NGAM_D1um","ICLIPAabcpp","MEOHtrpp","CYNTtex","Htex","FE2tex","CYTBD4um","PHOA510um","ZNabcpp","COLIPAabcex","CYOOum","PHOA430um","CO2tex","PIuabcpp","DALAabcpp","SUCRt2","CA2t2pp","PSICRum","PCHLDA430","SO4tex","2PGLYCtcx","ARGtex"],"format_type":"count","metric":0.12118226600985221},"test_find_constrained_transport_reactions":{"duration":0.0004551339999920856,"result":"passed","title":"Transport Reactions with Constraints","summary":"Cellular metabolism in any organism usually involves the transport of\nmetabolites across a lipid bi-layer. Hence, this test reports how many\nof these reactions, which transports metabolites from one compartment\nto another, have fixed constraints. This test does not have any mandatory\n'pass' criteria.\n\nImplementation:\nPlease refer to \"Transport Reactions\" for details on how memote identifies\ntransport reactions.\nFrom the pool of transport reactions identify reactions which are\nconstrained to values other than the model's median lower and upper bounds.","message":"A total of 0 (0.00%) transport reactions have fixed\nconstraints in the model:","data":[],"format_type":"count","metric":0.0},"test_transport_reaction_gpr_presence":{"duration":0.0005726840000193079,"result":"failed","title":"Fraction of Transport Reactions without GPR","summary":"As it is hard to identify the exact transport processes within a cell,\ntransport reactions are often added purely for modeling purposes.\nHighlighting where assumptions have been made versus where\nthere is proof may help direct the efforts to improve transport and\ntransport energetics of the tested metabolic model.\nHowever, transport reactions without GPR may also be valid:\nDiffusion, or known reactions with yet undiscovered genes likely lack GPR.\n\nImplementation:\nCheck which cobra.Reactions classified as transport reactions have a\nnon-empty \"gene_reaction_rule\" attribute.","message":"There are a total of 66 transport reactions (53.66% of all\ntransport reactions) without GPR:         PHOA550um, PHOA610um, PItex,\nNO2tex, HCO3tex, ...","data":["PHOA550um","PHOA610um","PItex","NO2tex","HCO3tex","PHOA410um","MOBDtex","O2tex","O2tcx","LEUtex","PHOA570um","3PGtcx","H2Otcx","HCO3tcx","NH4tex","PHOA630um","CU2tex","PHOA590um","Htcx","MNtex","CA2tex","Ktex","PQH2tcm","PHOA670um","SPMDtex","H2Otex","PHOA650um","PHOA490um","NO3tex","FE3tex","Zn2tex","CLtex","Htabcpp","O2tu","GLNtex","O2tpp","NI2tex","PHOA450um","PTRCtex","NGAM","CO2tpp","MEOHtex","PHOA470um","AGM4Pt2pp","PHOA690um","H2Otu_syn","H2Otpp","PQH2tum","AGMt2pp","RB15BPtcx","NAtex","PHOA530um","COBALT2tex","NGAM_D1um","MEOHtrpp","CYNTtex","Htex","FE2tex","PHOA510um","COLIPAabcex","PHOA430um","CO2tex","PSICRum","SO4tex","2PGLYCtcx","ARGtex"],"format_type":"percent","metric":0.5365853658536586},"test_find_reversible_oxygen_reactions":{"duration":0.022572807000017292,"result":"passed","title":"Number of Reversible Oxygen-Containing Reactions","summary":"The directionality of oxygen-producing/-consuming reactions affects the\nmodel's ability to grow anaerobically i.e. create faux-anaerobic organisms.\nThis test reports how many of these oxygen-containing reactions are\nreversible. This test does not have any mandatory 'pass' criteria.\n\nImplementation:\nFirst, find the metabolite representing atmospheric oxygen in the model on\nthe basis of an internal mapping table or by specifically looking for the\nformula \"O2\". Then, find all reactions that produce or consume oxygen and\nreport those that are reversible.","message":"There are a total of 8 reversible oxygen-containing reactions\n(19.05% of all oxygen-containing reactions): O2tex, EX_o2_e, GLXO3r,\nDESAT18a, O2tu, ...","data":["O2tex","EX_o2_e","GLXO3r","DESAT18a","O2tu","PDX5POi","O2tpp","DESAT16a"],"format_type":"count","metric":0.19047619047619047},"test_find_unique_metabolites":{"duration":0.11554446299999199,"result":"passed","title":"Unique Metabolites","summary":"Metabolites may be transported into different compartments, which means\nthat in a compartimentalized model the number of metabolites may be\nmuch higher than in a model with no compartments. This test counts only\none occurrence of each metabolite and returns this as the number of unique\nmetabolites. The test expects that the model is compartimentalized, and\nthus, that the number of unique metabolites is generally lower than the\ntotal number of metabolites.\n\nImplementation:\nReduce the list of metabolites to a unique set by removing the compartment\ntag. The cobrapy SBML parser adds compartment tags to each metabolite ID.","message":"Not counting the same entities in other compartments, there is a\ntotal of 784 (84.85%) unique metabolites in the model: pre3b,\nocte9coa, gua, pppg9, ahcys, 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Metabolites in Identical Compartments","summary":"The main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical metabolites from different namespaces\n(hence different IDs). This test therefore expects that every metabolite\nin any particular compartment has unique inchikey values.\n\nImplementation:\nIdentifies duplicate metabolites in each compartment by\ndetermining if any two metabolites have identical InChI-key annotations.\nFor instance, this function would find compounds with IDs ATP1 and ATP2 in\nthe cytosolic compartment, with both having the same InChI annotations.","message":"There are a total of 0 metabolites in the model which         have\nduplicates in the same compartment:","data":[],"format_type":"count","metric":0.0},"test_find_reactions_with_partially_identical_annotations":{"duration":0.11855029300005526,"result":"failed","title":"Reactions With Partially Identical Annotations","summary":"Identify reactions in a pairwise manner that are annotated\nwith identical database references. This does not take into account a\nreaction's directionality or compartment.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\nIt could also be useful to identify a 'type' of reaction that\noccurs in several compartments.\n\nImplementation:\n\nIdentify duplicate reactions globally by checking if any\ntwo metabolic reactions have the same entries in their annotation\nattributes. The heuristic looks at annotations with the keys\n\"metanetx.reaction\", \"kegg.reaction\", \"brenda\", \"rhea\", \"biocyc\",\n\"bigg.reaction\" only.","message":"Based on annotations there are 32 different groups of overlapping\nannotation which corresponds to a total of 71 duplicated reactions in\nthe model.","data":{"biocyc:META:TRANS-RXN-233,metanetx.reaction:MNXR100259":["EX_gln__L_e","GLNtex"],"metanetx.reaction:MNXR100484,rhea:28695,rhea:28696,rhea:28697,rhea:28698":["HCO3tex","EX_hco3_e"],"biocyc:META:RXN0-16,biocyc:META:TRANS-RXN0-487,metanetx.reaction:MNXR101670,rhea:28699,rhea:28700,rhea:28701,rhea:28702":["MNtex","EX_mn2_e"],"biocyc:META:RXN66-448,metanetx.reaction:MNXR95951,rhea:32143,rhea:32144,rhea:32145,rhea:32146":["ARGtex","EX_arg__L_e"],"biocyc:META:TRANS-RXN-145,biocyc:META:TRANS-RXN0-547,metanetx.reaction:MNXR98641,rhea:29667,rhea:29668,rhea:29669,rhea:29670":["H2Otpp","EX_h2o_e","H2Otex","H2Otu_syn"],"biocyc:META:RXN-14452,metanetx.reaction:MNXR100765,rhea:34979,rhea:34980,rhea:34981,rhea:34982":["Htex","EX_h_e"],"biocyc:META:TRANS-RXN0-474,metanetx.reaction:MNXR102090":["O2tex","O2tu","EX_o2_e","O2tpp"],"biocyc:META:TRANS-RXN-141,metanetx.reaction:MNXR101507,rhea:29827,rhea:29828,rhea:29829,rhea:29830":["MG2tex","EX_mg2_e"],"metanetx.reaction:MNXR103339":["PTRCtex","EX_ptrc_e"],"biocyc:META:RXN-9615,biocyc:META:TRANS-RXN0-206,biocyc:META:TRANS-RXN0-544,metanetx.reaction:MNXR101950,rhea:28747,rhea:28748,rhea:28749,rhea:28750":["NH4tex","NH4tpp","EX_nh4_e"],"biocyc:META:TRANS-RXN-144,biocyc:META:TRANS-RXN0-497,metanetx.reaction:MNXR96436,rhea:29671,rhea:29672,rhea:29673,rhea:29674":["EX_ca2_e","CA2tex"],"biocyc:META:TRANS-RXN0-545,metanetx.reaction:MNXR96810":["CO2tpp","CO2tex","EX_co2_e"],"biocyc:META:TRANS-RXN-8,metanetx.reaction:MNXR99505,rhea:28486,rhea:28487,rhea:28488,rhea:28489":["FE2tex","EX_fe2_e"],"biocyc:META:RXN0-14,metanetx.reaction:MNXR96951,rhea:28703,rhea:28704,rhea:28705,rhea:28706":["EX_cu2_e","CU2tex"],"biocyc:META:TRANS-RXN-143,biocyc:META:TRANS-RXN-185,biocyc:META:TRANS-RXN-186,biocyc:META:TRANS-RXN-187,biocyc:META:TRANS-RXN-190,metanetx.reaction:MNXR100950,rhea:29463,rhea:29464,rhea:29465,rhea:29466":["EX_k_e","Ktex"],"biocyc:META:RXN66-447,metanetx.reaction:MNXR101057":["LEUtex","EX_leu__L_e"],"biocyc:META:TRANS-RXN-141A,metanetx.reaction:MNXR96821,rhea:28578,rhea:28579,rhea:28580,rhea:28581":["COBALT2tex","EX_cobalt2_e"],"metanetx.reaction:MNXR101992,rhea:34923,rhea:34924,rhea:34925,rhea:34926":["NO3tex","EX_no3_e"],"biocyc:META:RXN0-12,metanetx.reaction:MNXR105280,rhea:29351,rhea:29352,rhea:29353,rhea:29354":["EX_zn2_e","Zn2tex"],"metanetx.reaction:MNXR99522,rhea:34971,rhea:34972,rhea:34973,rhea:34974":["FE3tex","EX_fe3_e"],"metanetx.reaction:MNXR104469,rhea:34983,rhea:34984,rhea:34985,rhea:34986":["EX_so4_e","SO4tex"],"metanetx.reaction:MNXR104495,rhea:35039,rhea:35040,rhea:35041,rhea:35042":["SPMDtex","EX_spmd_e"],"metanetx.reaction:MNXR101690,rhea:34907,rhea:34908,rhea:34909,rhea:34910":["EX_mobd_e","MOBDtex"],"biocyc:META:TRANS-RXN-141B,metanetx.reaction:MNXR101958,rhea:29831,rhea:29832,rhea:29833,rhea:29834":["NI2tex","EX_ni2_e"],"biocyc:META:TRANS-RXN-189,metanetx.reaction:MNXR101804,rhea:34963,rhea:34964,rhea:34965,rhea:34966":["NAtex","EX_na1_e"],"biocyc:META:TRANS-RXN-14,metanetx.reaction:MNXR96963":["EX_cynt_e","CYNTtex"],"biocyc:META:TRANS-RXN0-459,metanetx.reaction:MNXR101464,rhea:34871,rhea:34872,rhea:34873,rhea:34874":["MEOHtex","EX_meoh_e","MEOHtrpp"],"biocyc:META:TRANS-RXN0-470,metanetx.reaction:MNXR102871,rhea:32823,rhea:32824,rhea:32825,rhea:32826":["PItex","EX_pi_e"],"metanetx.reaction:MNXR95546":["AGM4PA","AGM4PApp"],"biocyc:META:TRANS-RXN-139,metanetx.reaction:MNXR96797,rhea:29823,rhea:29824,rhea:29825,rhea:29826":["EX_cl_e","CLtex"],"bigg.reaction:NDH_1_4_um":["NDH_1_4_um_copy2","NDH_1_4_um_copy1"],"bigg.reaction:NDH_1_1_um":["NDH_1_1_um_copy2","NDH_1_1_um_copy1"]},"format_type":"percent","metric":0.06995073891625615},"test_find_duplicate_reactions":{"duration":0.0018152459999782877,"result":"passed","title":"Duplicate Reactions","summary":"Identify reactions in a pairwise manner that use the same set\nof metabolites including potentially duplicate metabolites. Moreover, it\nwill take a reaction's directionality and compartment into account.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\n\nImplementation:\n\nCompare reactions in a pairwise manner.\nFor each reaction, the metabolite annotations are checked for a description\nof the structure (via InChI and InChIKey).If they exist, substrates and\nproducts as well as the stoichiometries of any reaction pair are compared.\nOnly reactions where the substrates, products, stoichiometry and\nreversibility are identical are considered to be duplicates.\nThis test will not be able to identify duplicate reactions if there are no\nstructure annotations. Further, it will report reactions with\ndiffering bounds as equal if they otherwise match the above conditions.","message":"Based on metabolites, directionality and compartment there are a\ntotal of 0 reactions in the model which have duplicates:","data":[],"format_type":"percent","metric":0.0},"test_find_reactions_with_identical_genes":{"duration":0.22828747099998736,"result":"failed","title":"Reactions With Identical Genes","summary":"Identify reactions in a pairwise manner that use identical\nsets of genes. It does *not* take into account a reaction's directionality,\ncompartment, metabolites or annotations.\n\nThe main reason for having this test is to help cleaning up merged models\nor models from automated reconstruction pipelines as these are prone to\nhaving identical reactions with identifiers from different namespaces.\n\nImplementation:\n\nCompare reactions in a pairwise manner and group reactions whose genes\nare identical. Skip reactions with missing genes.","message":"Based only on equal genes there are 94 different groups of\nidentical reactions which corresponds to a total of 274\nduplicated reactions in the model.","data":{"SYNPCC7942_RS00470":["URIDK2r","DTMPK"],"SYNPCC7942_RS07445":["ACOATA","KAS15"],"SYNPCC7942_RS04785":["3HAD180","3HAD60","3HAD80","3HAD120","3HAD140","3HAD40_2","OGMEACPD","3HAD160","3HAD100","OPMEACPD"],"SYNPCC7942_RS08210":["RNDR4","RNDR2","RNDR1","RNDR3"],"SYNPCC7942_RS07765":["HISTDb","HISTDa"],"SYNPCC7942_RS02095,SYNPCC7942_RS10880":["TRPS3","TRPS2","TRPS1"],"SYNPCC7942_RS05290":["HSTPT","PHETA1"],"SYNPCC7942_RS12700":["PCHLDA430","PCHLDA650","LPOR"],"SYNPCC7942_RS02490":["GCALDDy","ALDD2y","GLYALDDy"],"SYNPCC7942_RS13015":["DESAT18a","DESAT16a"],"SYNPCC7942_RS05420":["THZT","TMPPP_1"],"SYNPCC7942_RS12670":["NDPK7","NDPK3","NDPK2","NDPK5","NDPK1","NDPK6","NDPK8","NDPK4"],"SYNPCC7942_RS04030":["MTHFD","MTHFC"],"SYNPCC7942_RS10460":["LYCOPC","GCATENEC"],"SYNPCC7942_RS02020":["AICART","IMPC"],"SYNPCC7942_RS12930":["EHGLAT","ASPTA","TYRTA"],"SYNPCC7942_RS01465":["G1PACT","UAGDP"],"SYNPCC7942_RS02730":["3OAS60","3OAS80","OPMEACPS","3OAS160","KAS14","3OAS100","3OAS140","3OAS180","3OAS120","OGMEACPS"],"SYNPCC7942_RS10975":["AGTi","OHPBAT","SPTc"],"SYNPCC7942_RS03505":["3OAR140","3OAR160","3OAR100","3OAR80","3OAR180","3OAR60","OGMEACPR","3OAR120","3OAR40_2","OPMEACPR"],"SYNPCC7942_RS01045":["NAMNPP","NMNS"],"SYNPCC7942_RS08000":["PPK","PPK2"],"SYNPCC7942_RS10060":["PHYTES","PHYTES2_1"],"SYNPCC7942_RS04180":["SPS","SPP"],"SYNPCC7942_RS05900":["CYTK1","PANTS"],"SYNPCC7942_RS02075,SYNPCC7942_RS02720,SYNPCC7942_RS03350,SYNPCC7942_RS04735,SYNPCC7942_RS05140,SYNPCC7942_RS06400,SYNPCC7942_RS06405,SYNPCC7942_RS06760,SYNPCC7942_RS09705,SYNPCC7942_RS10390,SYNPCC7942_RS10395,SYNPCC7942_RS11800,SYNPCC7942_RS11900,SYNPCC7942_RS11905,SYNPCC7942_RS12755":["PSICSum","PSIum"],"SYNPCC7942_RS03035":["PFK","PFK_3"],"SYNPCC7942_RS10440":["P5CR","HPROb"],"SYNPCC7942_RS00360":["IPDPS_syn","DMPPS_syn"],"SYNPCC7942_RS08945":["ALAD_L","GLYDHDA"],"SYNPCC7942_RS00640":["EAR60y","EAR100y","EAR160y","EAR80y","EAR40y","EAR140y","EGMEACPR","EAR180y","EPMEACPR","EAR120y"],"SYNPCC7942_RS06730,SYNPCC7942_RS06735,SYNPCC7942_RS06740,SYNPCC7942_RS13075,SYNPCC7942_RS13080,SYNPCC7942_RS13085":["MNabc_1","ZNabcpp"],"SYNPCC7942_RS03210":["DHAD2","DHAD1"],"SYNPCC7942_RS02040,SYNPCC7942_RS05145":["ANS","ANS2"],"SYNPCC7942_RS01605":["ADSL1r","ADSL2r"],"SYNPCC7942_RS00540,SYNPCC7942_RS01040":["NMNAT","NNATr"],"SYNPCC7942_RS10055":["PDS2_1","PDS1_1","PHYPQOX"],"SYNPCC7942_RS07915":["KARI_1","KARA1","DPR","KARI_23dhmp_1"],"SYNPCC7942_RS02735":["TKT1","TKT2"],"SYNPCC7942_RS01490":["PPNCL2","PPCDC","PPNCL3"],"SYNPCC7942_RS08975,SYNPCC7942_RS08980":["CYTBD4um","CYTBD4cm"],"SYNPCC7942_RS09420":["TRSARyr","HPYRRy"],"SYNPCC7942_RS04025":["DMATT","GRTT","FRTT"],"SYNPCC7942_RS07385":["FBA3","FBA"],"SYNPCC7942_RS11515":["PTRCabcpp","SPMDabcpp"],"SYNPCC7942_RS10465":["NTD6","NTD7"],"SYNPCC7942_RS10115":["PRAMPC","PRATPP"],"SYNPCC7942_RS09615":["ACGS","ORNTAC"],"SYNPCC7942_RS09540":["ASPOb","ASPO6","ASPO5"],"SYNPCC7942_RS01255,SYNPCC7942_RS01260,SYNPCC7942_RS01265,SYNPCC7942_RS01270":["GLNabcpp","ARGabcpp"],"SYNPCC7942_RS12395":["BCAROHX2","BCAROHX"],"SYNPCC7942_RS07325":["GTPCII","DB4PS"],"SYNPCC7942_RS09670":["MPOMMM","MPOMOR_1","MPOMC1_1"],"SYNPCC7942_RS09625,SYNPCC7942_RS12945":["CITCIb","CITCIa","IPPMIa","IPPMIb"],"SYNPCC7942_RS07690":["IPMD","ERTHMMOR"],"SYNPCC7942_RS08860":["UM3PL","UM4PL","UAMAS"],"SYNPCC7942_RS00515,SYNPCC7942_RS01005":["NDHPQRum","NDHPQRcm"],"SYNPCC7942_RS00880,SYNPCC7942_RS04960":["BPNT2","BPNT"],"SYNPCC7942_RS07730":["ZCAROTDH1","ZCARDS"],"SYNPCC7942_RS10545":["PKETX","PKETF"],"SYNPCC7942_RS08020,SYNPCC7942_RS11780":["NI2uabcpp","CUabcpp"],"SYNPCC7942_RS02505":["RBFK","AFAT"],"SYNPCC7942_RS03225":["SPRMS","SPMS"],"SYNPCC7942_RS11240":["ADK1","DADK"],"SYNPCC7942_RS10670,SYNPCC7942_RS10675,Synpcc7942_2107":["NO2tabcpp","CYNTtabcpp"],"SYNPCC7942_RS00705,SYNPCC7942_RS12365":["ACHBSb","ACLSb","ACLSa"],"SYNPCC7942_RS01250,SYNPCC7942_RS09840":["E4PD","GAPD"],"SYNPCC7942_RS07455":["AGPATACP_HDE_PALM","AGPAT160","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","AGPAT161"],"SYNPCC7942_RS07440,SYNPCC7942_RS10435":["G3PAT161","G3PAT1819Z_1","G3PAT160"],"SYNPCC7942_RS04440":["GLUDGE_HDE_PALM","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_HDE"],"SYNPCC7942_RS05560":["GLUDGS_OLE_PALM","GLUDGS_HDE_HDE","GLUDGS_HDE_PALM","GLUDGS_OLE_HDE"],"SYNPCC7942_RS02045":["DAGK160","DAGK_OLE_PALM","DAGK161","DAGK_HDE_PALM","DAGK_OLE_HDE"],"SYNPCC7942_RS02945":["SQDGS_HDE_PALM","SQDGS_PALM_PALM"],"SYNPCC7942_RS05065":["DGDGS_OLE_HDE","DGDGS_HDE_PALM","DGDGS_HDE_HDE","DGDGS_OLE_PALM"],"SYNPCC7942_RS01760":["BTNPL2","BACCL"],"SYNPCC7942_RS07220":["LIPATPT_1","LIPAMPL_1"],"SYNPCC7942_RS03485":["ZXANHX","CXANHX"],"SYNPCC7942_RS08430,SYNPCC7942_RS11615":["ALCD1","ALCD19"],"SYNPCC7942_RS10140,SYNPCC7942_RS10355":["MPTG2","MPTG"],"SYNPCC7942_RS12230":["GLYCOX2","GLYCOX1"],"SYNPCC7942_RS05765,SYNPCC7942_RS06375":["OANTILpp","OANTIabcpp"],"SYNPCC7942_RS08520,SYNPCC7942_RS09815":["MDDCP5pp","MDDCP3pp","MDDCP2pp","MDDCP1pp","MDDCP4pp"],"SYNPCC7942_RS02000":["MLTGY2pp","MLTGY1pp","MLTGY3pp","MLTGY4pp"],"SYNPCC7942_RS11990":["AGM4PA","AM4PA","AM3PA"],"SYNPCC7942_RS10825":["AGM3PApp","AGM4PApp"],"SYNPCC7942_RS09960":["AGM4PCP","AM4PCP","UM4PCP","4PCP"],"SYNPCC7942_RS01800":["AGMH","AGM4PH","AGM3PH"],"SYNPCC7942_RS05285":["LEUTA","VALTA","ILETA"],"SYNPCC7942_RS02275,SYNPCC7942_RS04245,SYNPCC7942_RS04250,SYNPCC7942_RS05995,SYNPCC7942_RS06675,SYNPCC7942_RS11355":["4PEPTabcpp","ALAALAabcpp","DALAabcpp"],"SYNPCC7942_RS04020":["PAPA_OLE_PALM","PAPA_OLE_HDE","PAPA161","PAPA_HDE_PALM","PAPA160"],"SYNPCC7942_RS02455,SYNPCC7942_RS02950":["MCTP1App","MCTP1Bpp","MCTP2App"],"SYNPCC7942_RS00800,SYNPCC7942_RS05425":["THII","THISAT"],"SYNPCC7942_RS01140,SYNPCC7942_RS01145,SYNPCC7942_RS01500,SYNPCC7942_RS01750,SYNPCC7942_RS02165,SYNPCC7942_RS03355,SYNPCC7942_RS03360,SYNPCC7942_RS03570,SYNPCC7942_RS03575,SYNPCC7942_RS03585,SYNPCC7942_RS04600,SYNPCC7942_RS05330,SYNPCC7942_RS06020,SYNPCC7942_RS06025,SYNPCC7942_RS06030,SYNPCC7942_RS07110,SYNPCC7942_RS08350,SYNPCC7942_RS08550,SYNPCC7942_RS08555,SYNPCC7942_RS09545,SYNPCC7942_RS09955,SYNPCC7942_RS10225,SYNPCC7942_RS11400,SYNPCC7942_RS12590,SYNPCC7942_RS13675,SYNPCC7942_RS13745,SYNPCC7942_RS13795,Synpcc7942_2010":["PSIIum","PSIICSum"],"SYNPCC7942_RS00700,SYNPCC7942_RS01755,SYNPCC7942_RS09815":["MDDEP4pp","MDDEP3pp","MDDEP1pp","MDDEP2pp"]},"format_type":"percent","metric":0.26995073891625615},"test_find_medium_metabolites":{"duration":0.009040179000010085,"result":"failed","title":"Medium Components","summary":"This test checks all boundary reactions in the model that permit flux\ntowards creating a metabolite, and reports those metabolites. This test\ndoes not have any mandatory 'pass' criteria.\n\nImplementation:\nIdentify the metabolite IDs of each reaction in the method\ncobra.Model.medium. Model.medium returns exchange reactions whose bounds\npermit the uptake of metabolites.","message":null,"data":["hco3_e","mn2_e","mg2_e","ca2_e","nh4_e","cu2_e","k_e","h2o_e","o2_e","co2_e","leu__L_e","cobalt2_e","no3_e","zn2_e","fe3_e","so4_e","mobd_e","na1_e","h_e","photon410_e","photon430_e","photon450_e","photon470_e","photon490_e","photon510_e","photon530_e","photon550_e","photon570_e","photon590_e","photon610_e","photon630_e","photon650_e","photon670_e","photon690_e","pi_e","tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","his__L_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","no2_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e"],"format_type":"count","metric":1.0},"test_biomass_presence":{"duration":0.00021188700003449412,"result":"passed","title":"Biomass Reactions Identified","summary":"The biomass composition aka biomass formulation aka biomass reaction\nis a common pseudo-reaction accounting for biomass synthesis in\nconstraints-based modelling. It describes the stoichiometry of\nintracellular compounds that are required for cell growth. While this\nreaction may not be relevant to modeling the metabolism of higher\norganisms, it is essential for single-cell modeling.\n\nImplementation:\nIdentifies possible biomass reactions using two principal steps:\n    1. Return reactions that include the SBO annotation \"SBO:0000629\" for\n    biomass.\nIf no reactions can be identifies this way:\n    1. Look for the ``buzzwords`` \"biomass\", \"growth\" and \"bof\" in reaction\n    IDs.\n    2. Look for metabolite IDs or names that contain the ``buzzword``\n    \"biomass\" and obtain the set of reactions they are involved in.\n    3. Remove boundary reactions from this set.\n    4. Return the union of reactions that match the buzzwords and of the\n    reactions that metabolites are involved in that match the buzzword.\nThis test checks if at least one biomass reaction is present.","message":"In this model 9 the following biomass reactions were\nidentified: BIOMASS_CARB, BIOMASS_CELL_WALL, BIOMASS_COFACTORS,\nBIOMASS_DNA, BIOMASS_MEM_LIPIDS, ...","data":["BIOMASS_CARB","BIOMASS_CELL_WALL","BIOMASS_COFACTORS","BIOMASS_DNA","BIOMASS_MEM_LIPIDS","BIOMASS_PIGMENTS","BIOMASS_PROTEIN","BIOMASS_RNA","BIOMASS__1"],"format_type":"count","metric":0.0},"test_biomass_consistency":{"duration":{"BIOMASS_CARB":0.0002266850000296472,"BIOMASS_CELL_WALL":0.0002544370000236995,"BIOMASS_COFACTORS":0.00034670099995537385,"BIOMASS_DNA":0.00025920699999915087,"BIOMASS_MEM_LIPIDS":0.00023912900002187598,"BIOMASS_PIGMENTS":0.00026370499995209684,"BIOMASS_PROTEIN":0.00020616699998754484,"BIOMASS_RNA":0.00022226799995905822,"BIOMASS__1":0.00026587799999333583},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"failed"},"title":"Biomass Consistency","summary":"This test only yields sensible results if all biomass precursor\nmetabolites have chemical formulas assigned to them.\nThe molecular weight of the biomass reaction in metabolic models is\ndefined to be equal to 1 g/mmol. Conforming to this is essential in order\nto be able to reliably calculate growth yields, to cross-compare models,\nand to obtain valid predictions when simulating microbial consortia. A\ndeviation from 1 - 1E-03 to 1 + 1E-06 is accepted.\n\nImplementation:\nMultiplies the coefficient of each metabolite of the biomass reaction with\nits molecular weight calculated from the formula, then divides the overall\nsum of all the products by 1000.","message":{"BIOMASS_CARB":"One or more of the biomass components do not have a defined\nformula or contain unspecified chemical groups.","BIOMASS_CELL_WALL":"The component molar mass of the biomass reaction BIOMASS_CELL_WALL\nsums up to 0.57142989442176             which is outside of the 1e-03\nmargin from 1 mmol / g[CDW] / h.","BIOMASS_COFACTORS":"The component molar mass of the biomass reaction BIOMASS_COFACTORS\nsums up to 1.0009205772282002             which is outside of the\n1e-03 margin from 1 mmol / g[CDW] / h.","BIOMASS_DNA":"The component molar mass of the biomass reaction BIOMASS_DNA sums up\nto 1.00000345570174             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS_MEM_LIPIDS":"The component molar mass of the biomass reaction BIOMASS_MEM_LIPIDS\nsums up to 1.0000000000161593             which is outside of the\n1e-03 margin from 1 mmol / g[CDW] / h.","BIOMASS_PIGMENTS":"The component molar mass of the biomass reaction BIOMASS_PIGMENTS sums\nup to 1.000569280708             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS_PROTEIN":"One or more of the biomass components do not have a defined\nformula or contain unspecified chemical groups.","BIOMASS_RNA":"The component molar mass of the biomass reaction BIOMASS_RNA sums up\nto 0.9999955663688002             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h.","BIOMASS__1":"The component molar mass of the biomass reaction BIOMASS__1 sums up to\n4.547473508864641e-16             which is outside of the 1e-03 margin\nfrom 1 mmol / g[CDW] / h."},"data":{"BIOMASS_CARB":null,"BIOMASS_CELL_WALL":0.57142989442176,"BIOMASS_COFACTORS":1.0009205772282002,"BIOMASS_DNA":1.00000345570174,"BIOMASS_MEM_LIPIDS":1.0000000000161593,"BIOMASS_PIGMENTS":1.000569280708,"BIOMASS_PROTEIN":null,"BIOMASS_RNA":0.9999955663688002,"BIOMASS__1":4.547473508864641e-16},"format_type":"number","metric":{"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_RNA":0.0,"BIOMASS__1":1.0},"score":{"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_RNA":1.0,"BIOMASS__1":0.0}},"test_biomass_default_production":{"duration":{"BIOMASS_CARB":0.004545718000031229,"BIOMASS_CELL_WALL":0.0027561209999475977,"BIOMASS_COFACTORS":0.002763865000019905,"BIOMASS_DNA":0.00275947699998369,"BIOMASS_MEM_LIPIDS":0.0027615710000077343,"BIOMASS_PIGMENTS":0.002721866999991107,"BIOMASS_PROTEIN":0.00275191299999733,"BIOMASS_RNA":0.0027681830000005903,"BIOMASS__1":0.0027559299999779796},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Biomass Production In Default Medium","summary":"Using flux balance analysis this test optimizes the model for growth in\nthe medium that is set by default. Any non-zero growth rate is accepted to\npass this test.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and the model's default constraints.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.005266338786562521","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.004285301264398366","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 6.414476106457932e-05","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.00039349307207683107","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.00857060252879673","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.0010618922630018588","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN this is the growth rate\n(1/h) that         can be achieved when the model is simulated on the\nprovided         default medium: 0.027555295677489867","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.006123399039442193","BIOMASS__1":"Using the biomass reaction BIOMASS__1 this is the growth rate (1/h)\nthat         can be achieved when the model is simulated on the\nprovided         default medium: 0.053903160558470005"},"data":{"BIOMASS_CARB":0.005266338786562521,"BIOMASS_CELL_WALL":0.004285301264398366,"BIOMASS_COFACTORS":6.414476106457932e-05,"BIOMASS_DNA":0.00039349307207683107,"BIOMASS_MEM_LIPIDS":0.00857060252879673,"BIOMASS_PIGMENTS":0.0010618922630018588,"BIOMASS_PROTEIN":0.027555295677489867,"BIOMASS_RNA":0.006123399039442193,"BIOMASS__1":0.053903160558470005},"format_type":"number","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_open_production":{"duration":{"BIOMASS_CARB":0.018875600999990638,"BIOMASS_CELL_WALL":0.005372990000012123,"BIOMASS_COFACTORS":0.0053004540000074485,"BIOMASS_DNA":0.005344496999953208,"BIOMASS_MEM_LIPIDS":0.005312255000035293,"BIOMASS_PIGMENTS":0.005347282000002451,"BIOMASS_PROTEIN":0.005303088999994543,"BIOMASS_RNA":0.005383830999960537,"BIOMASS__1":0.005331872999988718},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Biomass Production In Complete Medium","summary":"Using flux balance analysis this test optimizes the model for growth using\na complete medium i.e. unconstrained boundary reactions. Any non-zero\ngrowth rate is accepted to pass this test.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and after removing any constraints from all boundary reactions.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n9.044461745820453","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n7.359618309034922","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n0.1101628400975043","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n0.675788851018302","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n14.7192366180699","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n1.8237041595973353","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN this is the growth rate\nthat can be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n47.323734334322836","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA this is the growth rate that\ncan be         achieved when the model is simulated on a complete\nmedium i.e.         with all the boundary reactions unconstrained:\n10.516385407627276","BIOMASS__1":"Using the biomass reaction BIOMASS__1 this is the growth rate that can\nbe         achieved when the model is simulated on a complete medium\ni.e.         with all the boundary reactions unconstrained:\n92.57381520798678"},"data":{"BIOMASS_CARB":9.044461745820453,"BIOMASS_CELL_WALL":7.359618309034922,"BIOMASS_COFACTORS":0.1101628400975043,"BIOMASS_DNA":0.675788851018302,"BIOMASS_MEM_LIPIDS":14.7192366180699,"BIOMASS_PIGMENTS":1.8237041595973353,"BIOMASS_PROTEIN":47.323734334322836,"BIOMASS_RNA":10.516385407627276,"BIOMASS__1":92.57381520798678},"format_type":"number","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_precursors_default_production":{"duration":{"BIOMASS_CARB":0.1021076050000147,"BIOMASS_CELL_WALL":0.10662955899999815,"BIOMASS_COFACTORS":0.4247433669999623,"BIOMASS_DNA":0.1436751780000236,"BIOMASS_MEM_LIPIDS":0.21819467299997086,"BIOMASS_PIGMENTS":0.1636616389999972,"BIOMASS_PROTEIN":0.3045837579999784,"BIOMASS_RNA":0.1286314370000241,"BIOMASS__1":0.18940635600000633},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Blocked Biomass Precursors In Default Medium","summary":"Using flux balance analysis this test optimizes for the production of each\nmetabolite that is a substrate of the biomass reaction with the exception\nof atp and h2o. Optimizations are carried out using the default\nconditions. This is useful when reconstructing the precursor biosynthesis\npathways of a metabolic model. To pass this test, the model should be able\nto synthesis all the precursors.\n\nImplementation:\nFor each biomass precursor (except ATP and H2O) add a temporary demand\nreaction, then carry out FBA with this reaction as the objective. Collect\nall metabolites for which this optimization is equal to zero or\ninfeasible.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated on the         provided default medium a total of 0\nprecursors         (0.00% of all precursors except h2o and atp) cannot\nbe produced: []","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated on the         provided default medium a total of 20\nprecursors         (95.24% of all precursors except h2o and atp)\ncannot be produced: ['lystrna_c', 'alatrna_c', 'asptrna_c',\n'mettrna_c', 'phetrna_c', 'glntrna_c', 'valtrna_c', 'cystrna_c',\n'thrtrna_c', 'sertrna_c', 'leutrna_c', 'histrna_c', 'glytrna_c',\n'argtrna_c', 'iletrna_c', 'protrna_c', 'tyrtrna_c', 'asntrna_c',\n'trptrna_c', 'glutrna_c']","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\non the         provided default medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []"},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":[],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":["lystrna_c","alatrna_c","asptrna_c","mettrna_c","phetrna_c","glntrna_c","valtrna_c","cystrna_c","thrtrna_c","sertrna_c","leutrna_c","histrna_c","glytrna_c","argtrna_c","iletrna_c","protrna_c","tyrtrna_c","asntrna_c","trptrna_c","glutrna_c"],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"count","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.9523809523809523,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.04761904761904767,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_biomass_precursors_open_production":{"duration":{"BIOMASS_CARB":0.09046383100002231,"BIOMASS_CELL_WALL":0.10775202400003536,"BIOMASS_COFACTORS":0.3934381409999901,"BIOMASS_DNA":0.13706856800001788,"BIOMASS_MEM_LIPIDS":0.19485785099999475,"BIOMASS_PIGMENTS":0.16903250100000378,"BIOMASS_PROTEIN":0.1807595859999651,"BIOMASS_RNA":0.1251877760000184,"BIOMASS__1":0.18367423699999108},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Blocked Biomass Precursors In Complete Medium","summary":"Using flux balance analysis this test optimizes for the production of each\nmetabolite that is a substrate of the biomass reaction with the exception\nof atp and h2o. Optimizations are carried out using a complete\nmedium i.e. unconstrained boundary reactions. This is useful when\nreconstructing the precursor biosynthesis pathways of a metabolic model.\nTo pass this test, the model should be able to synthesis all the\nprecursors.\n\nImplementation:\nFirst remove any constraints from all boundary reactions, then for each\nbiomass precursor (except ATP and H2O) add a temporary demand\nreaction, then carry out FBA with this reaction as the objective. Collect\nall metabolites for which this optimization is below or equal to zero or is\ninfeasible.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated in         complete medium a total of 0 precursors\n(0.00% of all precursors except h2o and atp) cannot be produced: []","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated in         complete medium a total of 20 precursors\n(95.24% of all precursors except h2o and atp) cannot be produced:\n['lystrna_c', 'alatrna_c', 'asptrna_c', 'mettrna_c', 'phetrna_c',\n'glntrna_c', 'valtrna_c', 'cystrna_c', 'thrtrna_c', 'sertrna_c',\n'leutrna_c', 'histrna_c', 'glytrna_c', 'argtrna_c', 'iletrna_c',\n'protrna_c', 'tyrtrna_c', 'asntrna_c', 'trptrna_c', 'glutrna_c']","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\nin         complete medium a total of 0 precursors         (0.00% of\nall precursors except h2o and atp) cannot be produced: []"},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":[],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":["lystrna_c","alatrna_c","asptrna_c","mettrna_c","phetrna_c","glntrna_c","valtrna_c","cystrna_c","thrtrna_c","sertrna_c","leutrna_c","histrna_c","glytrna_c","argtrna_c","iletrna_c","protrna_c","tyrtrna_c","asntrna_c","trptrna_c","glutrna_c"],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"count","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.9523809523809523,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.04761904761904767,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_gam_in_biomass":{"duration":{"BIOMASS_CARB":0.09921336599995811,"BIOMASS_CELL_WALL":0.10054016600003024,"BIOMASS_COFACTORS":0.09957034600000725,"BIOMASS_DNA":0.09933172700004889,"BIOMASS_MEM_LIPIDS":0.10004934500000218,"BIOMASS_PIGMENTS":0.09912960799999837,"BIOMASS_PROTEIN":0.09935238600002094,"BIOMASS_RNA":0.09751375500002268,"BIOMASS__1":0.09763487300000406},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"failed","BIOMASS__1":"passed"},"title":"Growth-associated Maintenance in Biomass Reaction","summary":"The growth-associated maintenance (GAM) term accounts for the energy in\nthe form of ATP that is required to synthesize macromolecules such as\nProteins, DNA and RNA, and other processes during growth. A GAM term is\ntherefore a requirement for any well-defined biomass reaction. There are\ndifferent ways to implement this term depending on\nwhat kind of experimental data is available and the preferred\nway of implementing the biomass reaction:\n- Chemostat growth experiments yield a single GAM value representing the\n  required energy per gram of biomass (Figure 6 of [1]_). This can be\n  implemented in a lumped biomass reaction or in the final term of a split\n  biomass reaction.\n- Experimentally delineating or estimating the GAM requirements\n  for each macromolecule separately is possible, yet requires either\n  data from multi-omics experiments [2]_ or detailed resources [1]_ ,\n  respectively. Individual energy requirements can either be implemented\n  in a split biomass equation on the term for each macromolecule, or, on\n  the basis of the biomass composition, they can be summed into a single\n  GAM value for growth and treated as mentioned above.\n\nThis test is only able to detect if a lumped biomass reaction or the final\nterm of a split biomass reaction contains this term. Hence, it will\nonly detect the use of a single GAM value as opposed to individual energy\nrequirements of each macromolecule. Both approaches, however, have\nits merits.\n\nImplementation:\nDetermines the metabolite identifiers of ATP, ADP, H2O, HO4P and H+ based\non an internal mapping table. Checks if ATP and H2O are a subset of the\nreactants and ADP, HO4P and H+ a subset of the products of the biomass\nreaction.\n\nReferences:\n.. [1] Thiele, I., & Palsson, B. Ø. (2010, January). A protocol for\n       generating a high-quality genome-scale metabolic reconstruction.\n       Nature protocols. Nature Publishing Group.\n       http://doi.org/10.1038/nprot.2009.203\n.. [2] Hackett, S. R., Zanotelli, V. R. T., Xu, W., Goya, J., Park, J. O.,\n       Perlman, D. H., Gibney, P. A., Botstein, D., Storey, J. D.,\n       Rabinowitz, J. D.  (2010, January). Systems-level analysis of\n       mechanisms regulating yeast metabolic flux\n       Science\n       http://doi.org/10.1126/science.aaf2786","message":{"BIOMASS_CARB":"No, BIOMASS_CARB does not contain a term for growth-associated\nmaintenance.","BIOMASS_CELL_WALL":"No, BIOMASS_CELL_WALL does not contain a term for growth-associated\nmaintenance.","BIOMASS_COFACTORS":"No, BIOMASS_COFACTORS does not contain a term for growth-associated\nmaintenance.","BIOMASS_DNA":"No, BIOMASS_DNA does not contain a term for growth-associated\nmaintenance.","BIOMASS_MEM_LIPIDS":"No, BIOMASS_MEM_LIPIDS does not contain a term for growth-associated\nmaintenance.","BIOMASS_PIGMENTS":"No, BIOMASS_PIGMENTS does not contain a term for growth-associated\nmaintenance.","BIOMASS_PROTEIN":"Yes, BIOMASS_PROTEIN contains a term for growth-associated\nmaintenance.","BIOMASS_RNA":"No, BIOMASS_RNA does not contain a term for growth-associated\nmaintenance.","BIOMASS__1":"Yes, BIOMASS__1 contains a term for growth-associated maintenance."},"data":{"BIOMASS_CARB":false,"BIOMASS_CELL_WALL":false,"BIOMASS_COFACTORS":false,"BIOMASS_DNA":false,"BIOMASS_MEM_LIPIDS":false,"BIOMASS_PIGMENTS":false,"BIOMASS_PROTEIN":true,"BIOMASS_RNA":false,"BIOMASS__1":true},"format_type":"raw","metric":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":1.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":0.0,"BIOMASS__1":1.0}},"test_fast_growth_default":{"duration":{"BIOMASS_CARB":0.018254768000019794,"BIOMASS_CELL_WALL":0.0028371860000220295,"BIOMASS_COFACTORS":0.002791460000025836,"BIOMASS_DNA":0.002855560999989848,"BIOMASS_MEM_LIPIDS":0.0028242619999900853,"BIOMASS_PIGMENTS":0.002839601000005132,"BIOMASS_PROTEIN":0.0027844970000501235,"BIOMASS_RNA":0.002832637999972576,"BIOMASS__1":0.002810866000004353},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"failed","BIOMASS__1":"failed"},"title":"Unrealistic Growth Rate In Default Medium","summary":"The growth rate of a metabolic model should not be faster than that of the\nfastest growing organism. This is based on a doubling time of Vibrio\nnatriegens which was reported to be 14.8 minutes by: Henry H. Lee, Nili\nOstrov, Brandon G. Wong, Michaela A. Gold, Ahmad S. Khalil,\nGeorge M. Church\nin https://www.biorxiv.org/content/biorxiv/early/2016/06/12/058487.full.pdf\n\nThe calculation ln(2)/(14.8/60) ~ 2.81 yields the corresponding growth\nrate.\n\nImplementation:\nCalculate the solution of FBA with the biomass reaction set as objective\nfunction and a model's default constraints. Then check if the objective\nvalue is higher than 2.81.","message":{"BIOMASS_CARB":"Using the biomass reaction BIOMASS_CARB and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_CELL_WALL":"Using the biomass reaction BIOMASS_CELL_WALL and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_COFACTORS":"Using the biomass reaction BIOMASS_COFACTORS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_DNA":"Using the biomass reaction BIOMASS_DNA and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms.","BIOMASS_MEM_LIPIDS":"Using the biomass reaction BIOMASS_MEM_LIPIDS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_PIGMENTS":"Using the biomass reaction BIOMASS_PIGMENTS and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_PROTEIN":"Using the biomass reaction BIOMASS_PROTEIN and when the model is\nsimulated on             the provided default medium the growth rate\nis *lower* than that             of the fastest bacteria. This is to\nbe expected for             a majority of organisms.","BIOMASS_RNA":"Using the biomass reaction BIOMASS_RNA and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms.","BIOMASS__1":"Using the biomass reaction BIOMASS__1 and when the model is simulated\non             the provided default medium the growth rate is *lower*\nthan that             of the fastest bacteria. This is to be expected\nfor             a majority of organisms."},"data":{"BIOMASS_CARB":false,"BIOMASS_CELL_WALL":false,"BIOMASS_COFACTORS":false,"BIOMASS_DNA":false,"BIOMASS_MEM_LIPIDS":false,"BIOMASS_PIGMENTS":false,"BIOMASS_PROTEIN":false,"BIOMASS_RNA":false,"BIOMASS__1":false},"format_type":"raw","metric":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":1.0,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0},"score":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.0,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0}},"test_direct_metabolites_in_biomass":{"duration":{"BIOMASS_CARB":0.09020959299999731,"BIOMASS_CELL_WALL":0.08939811999999847,"BIOMASS_COFACTORS":0.08884601399995518,"BIOMASS_DNA":0.09344850400003679,"BIOMASS_MEM_LIPIDS":0.09100408400001925,"BIOMASS_PIGMENTS":0.08796165400002565,"BIOMASS_PROTEIN":0.08788308599997663,"BIOMASS_RNA":0.0879663320000077,"BIOMASS__1":0.0880986999999891},"result":{"BIOMASS_CARB":"passed","BIOMASS_CELL_WALL":"passed","BIOMASS_COFACTORS":"passed","BIOMASS_DNA":"passed","BIOMASS_MEM_LIPIDS":"passed","BIOMASS_PIGMENTS":"passed","BIOMASS_PROTEIN":"passed","BIOMASS_RNA":"passed","BIOMASS__1":"passed"},"title":"Ratio of Direct Metabolites in Biomass Reaction","summary":"Some biomass precursors are taken from the media and directly consumed by\nthe biomass reaction. It might not be a problem for ions or\nmetabolites for which the organism in question is auxotrophic. However,\ntoo many of these metabolites may be artifacts of automated gap-filling\nprocedures. Many gap-filling algorithms attempt to minimise the number of\nadded reactions. This can lead to many biomass precursors being\n\"direct metabolites\".\n\nThis test reports the ratio of direct metabolites to the total amount of\nprecursors to a given biomass reaction. It specifically looks for\nmetabolites that are only in either exchange, transport or biomass\nreactions. Bear in mind that this may lead to false positives in heavily\ncompartimentalized models.\n\nTo pass this test, the ratio of direct metabolites should be less than 50%\nof all biomass precursors. This is an arbitrary threshold but it takes\ninto account that while certain ions do not serve a relevant metabolic\nfunction, it may still be important to include them in the biomass\nreaction to account for the impact of their uptake energy costs.\n\nThis threshold is subject to change in the future.\n\nImplementation:\nIdentify biomass precursors (excluding ATP and H+), identify cytosol\nand extracellular compartment from an internal mapping table. Then,\ndetermine which precursors is only involved in transport, boundary and\nbiomass reactions. Using FBA with the biomass function as the objective\nthen determine whether the metabolite is taken up only to be consumed by\nthe biomass reaction.","message":{"BIOMASS_CARB":"BIOMASS_CARB contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_CELL_WALL":"BIOMASS_CELL_WALL contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_COFACTORS":"BIOMASS_COFACTORS contains a total of 2 direct metabolites (7.69%).\nSpecifically these are: ['k_c', 'na1_c'].","BIOMASS_DNA":"BIOMASS_DNA contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_MEM_LIPIDS":"BIOMASS_MEM_LIPIDS contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_PIGMENTS":"BIOMASS_PIGMENTS contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_PROTEIN":"BIOMASS_PROTEIN contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS_RNA":"BIOMASS_RNA contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: [].","BIOMASS__1":"BIOMASS__1 contains a total of 0 direct metabolites (0.00%).\nSpecifically these are: []."},"data":{"BIOMASS_CARB":[],"BIOMASS_CELL_WALL":[],"BIOMASS_COFACTORS":["k_c","na1_c"],"BIOMASS_DNA":[],"BIOMASS_MEM_LIPIDS":[],"BIOMASS_PIGMENTS":[],"BIOMASS_PROTEIN":[],"BIOMASS_RNA":[],"BIOMASS__1":[]},"format_type":"percent","metric":{"BIOMASS_CARB":0.0,"BIOMASS_CELL_WALL":0.0,"BIOMASS_COFACTORS":0.07692307692307693,"BIOMASS_DNA":0.0,"BIOMASS_MEM_LIPIDS":0.0,"BIOMASS_PIGMENTS":0.0,"BIOMASS_PROTEIN":0.0,"BIOMASS_RNA":0.0,"BIOMASS__1":0.0},"score":{"BIOMASS_CARB":1.0,"BIOMASS_CELL_WALL":1.0,"BIOMASS_COFACTORS":0.9230769230769231,"BIOMASS_DNA":1.0,"BIOMASS_MEM_LIPIDS":1.0,"BIOMASS_PIGMENTS":1.0,"BIOMASS_PROTEIN":1.0,"BIOMASS_RNA":1.0,"BIOMASS__1":1.0}},"test_essential_precursors_not_in_biomass":{"duration":{"BIOMASS_CARB":0.8835561860000212,"BIOMASS_CELL_WALL":0.8829994540000143,"BIOMASS_COFACTORS":0.7773721890000047,"BIOMASS_DNA":0.885594866999952,"BIOMASS_MEM_LIPIDS":0.8838829229999874,"BIOMASS_PIGMENTS":0.8811422799999491,"BIOMASS_PROTEIN":0.7643074060000004,"BIOMASS_RNA":0.8854645649999497,"BIOMASS__1":0.881920373000014},"result":{"BIOMASS_CARB":"failed","BIOMASS_CELL_WALL":"failed","BIOMASS_COFACTORS":"failed","BIOMASS_DNA":"failed","BIOMASS_MEM_LIPIDS":"failed","BIOMASS_PIGMENTS":"failed","BIOMASS_PROTEIN":"failed","BIOMASS_RNA":"failed","BIOMASS__1":"failed"},"title":"Number of Missing Essential Biomass Precursors","summary":"There are universal components of life that make up the biomass of all\nknown organisms. These include all proteinogenic amino acids, deoxy- and\nribonucleotides, water and a range of metabolic cofactors.\n\nThis test reports the amount of biomass precursors that have been reported\nto be essential constituents of the biomass equation. All of the following\nprecursors need to be included in the biomass reaction to pass the test:\n\nAminoacids:\ntrp__L, cys__L, his__L, tyr__L, met__L, phe__L, ser__L, pro__L, asp__L,\nthr__L, gln__L, glu__L, ile__L, arg__L, lys__L, val__L, leu__L, ala__L,\ngly, asn__L\nDNA: datp, dctp, dttp, dgtp\nRNA: atp, ctp, utp, gtp\nCofactors: nad, nadp, amet, fad, pydx5p, coa, thmpp, fmn and h2o\n\nThese metabolites were selected based on the results presented by\nDOI:10.1016/j.ymben.2016.12.002\n\nPlease note, that the authors also suggest to count C1 carriers\n(derivatives of tetrahydrofolate(B9) or tetrahydromethanopterin) as\nuniversal cofactors. We have omitted these from this check because there\nare many individual compounds that classify as C1 carriers, and it is not\nclear a priori which one should be preferred. In a future update, we may\nconsider identifying these using a chemical ontology.\n\nImplementation:\nDetermine whether the model employs a lumped or split biomass reaction.\nThen, using an internal mapping table, try to identify the above list of\nessential precursors in list of precursor metabolites of either type of\nbiomass reaction. List IDs in the models namespace if the metabolite\nexists, else use the MetaNetX namespace if the metabolite does not exist\nin the model. Identifies the cytosol from an internal mapping\ntable, and assumes that all precursors exist in that compartment.","message":{"BIOMASS_CARB":"BIOMASS_CARB lacks a total of 35 essential metabolites\n(1750.00% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_CELL_WALL":"BIOMASS_CELL_WALL lacks a total of 35 essential metabolites\n(1750.00% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_COFACTORS":"BIOMASS_COFACTORS lacks a total of 31 essential metabolites\n(119.23% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'atp_c', 'gtp_c', 'ctp_c', 'utp_c',\n'amet_c', 'fmn_c', 'h2o_c'].","BIOMASS_DNA":"BIOMASS_DNA lacks a total of 2 essential metabolites         (50.00%\nof all biomass precursors). Specifically         these are:\n['pydx5p_c', 'thmpp_c'].","BIOMASS_MEM_LIPIDS":"BIOMASS_MEM_LIPIDS lacks a total of 35 essential metabolites\n(318.18% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'nadp_c', 'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_PIGMENTS":"BIOMASS_PIGMENTS lacks a total of 34 essential metabolites\n(485.71% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'gtp_c', 'ctp_c', 'utp_c', 'nad_c',\n'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_PROTEIN":"BIOMASS_PROTEIN lacks a total of 34 essential metabolites\n(161.90% of all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'datp_c',\n'dctp_c', 'dttp_c', 'dgtp_c', 'ctp_c', 'utp_c', 'nad_c', 'nadp_c',\n'amet_c', 'fad_c', 'pydx5p_c', 'coa_c', 'thmpp_c', 'fmn_c'].","BIOMASS_RNA":"BIOMASS_RNA lacks a total of 2 essential metabolites         (66.67%\nof all biomass precursors). Specifically         these are:\n['pydx5p_c', 'thmpp_c'].","BIOMASS__1":"BIOMASS__1 lacks a total of 22 essential metabolites         (275.00%\nof all biomass precursors). Specifically         these are:\n['trp__L_c', 'cys__L_c', 'his__L_c', 'tyr__L_c', 'met__L_c',\n'phe__L_c', 'ser__L_c', 'pro__L_c', 'asp__L_c', 'thr__L_c',\n'gln__L_c', 'glu__L_c', 'ile__L_c', 'arg__L_c', 'lys__L_c',\n'val__L_c', 'leu__L_c', 'ala__L_c', 'gly_c', 'asn__L_c', 'amet_c',\n'fmn_c']."},"data":{"BIOMASS_CARB":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_CELL_WALL":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_COFACTORS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","atp_c","gtp_c","ctp_c","utp_c","amet_c","fmn_c","h2o_c"],"BIOMASS_DNA":["pydx5p_c","thmpp_c"],"BIOMASS_MEM_LIPIDS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_PIGMENTS":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","gtp_c","ctp_c","utp_c","nad_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_PROTEIN":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","datp_c","dctp_c","dttp_c","dgtp_c","ctp_c","utp_c","nad_c","nadp_c","amet_c","fad_c","pydx5p_c","coa_c","thmpp_c","fmn_c"],"BIOMASS_RNA":["pydx5p_c","thmpp_c"],"BIOMASS__1":["trp__L_c","cys__L_c","his__L_c","tyr__L_c","met__L_c","phe__L_c","ser__L_c","pro__L_c","asp__L_c","thr__L_c","gln__L_c","glu__L_c","ile__L_c","arg__L_c","lys__L_c","val__L_c","leu__L_c","ala__L_c","gly_c","asn__L_c","amet_c","fmn_c"]},"format_type":"count","metric":{"BIOMASS_CARB":17.5,"BIOMASS_CELL_WALL":17.5,"BIOMASS_COFACTORS":1.1923076923076923,"BIOMASS_DNA":0.5,"BIOMASS_MEM_LIPIDS":3.1818181818181817,"BIOMASS_PIGMENTS":4.857142857142857,"BIOMASS_PROTEIN":1.619047619047619,"BIOMASS_RNA":0.6666666666666666,"BIOMASS__1":2.75},"score":{"BIOMASS_CARB":-16.5,"BIOMASS_CELL_WALL":-16.5,"BIOMASS_COFACTORS":-0.1923076923076923,"BIOMASS_DNA":0.5,"BIOMASS_MEM_LIPIDS":-2.1818181818181817,"BIOMASS_PIGMENTS":-3.8571428571428568,"BIOMASS_PROTEIN":-0.6190476190476191,"BIOMASS_RNA":0.33333333333333337,"BIOMASS__1":-1.75}},"test_stoichiometric_consistency":{"duration":1.0159147640000015,"result":"failed","title":"Stoichiometric Consistency","summary":"Stoichiometric inconsistency violates universal constraints:\n1. Molecular masses are always positive, and\n2. On each side of a reaction the mass is conserved.\nA single incorrectly defined reaction can lead to stoichiometric\ninconsistency in the model, and consequently to unconserved metabolites.\nSimilar to insufficient constraints, this may give rise to cycles which\neither produce mass from nothing or consume mass from the model.\n\nImplementation:\nThis test uses an implementation of the algorithm presented in\nsection 3.1 by Gevorgyan, A., M. G Poolman, and D. A Fell.\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425","message":"This model's stoichiometry inconsistent","data":false,"format_type":"percent","metric":1.0},"test_unconserved_metabolites":{"duration":2.6730668870000045,"result":"failed","title":"Unconserved Metabolites","summary":"The list of unconserved metabolites is computed using the algorithm described\nin section 3.2 of\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425.","message":"This model contains 34 unconserved metabolites: o2_cx, o2_e, o2_p,\no2_c, h_p, ...","data":["o2_cx","o2_e","o2_p","o2_c","h_p","o2_u","h2o2_c","o2s_c","photon410_e","photon430_e","h2_c","photon450_e","photon470_e","h2o_u","photon490_e","photon510_e","h_u","photon530_e","photon550_e","photon570_e","h_e","photon590_e","h2o_cx","photon610_e","h_cx","photon630_e","h2o_c","photon650_e","photon670_e","photon690_e","h_c","h2o_p","pho_loss_c","h2o_e"],"format_type":"count","metric":34},"test_inconsistent_min_stoichiometry":{"duration":7.28956006300001,"result":"failed","title":"Minimal Inconsistent Net Stoichiometries","summary":"Only 10 unconserved metabolites are reported and considered to\navoid computing for too long.\n\nImplementation:\nAlgorithm described in section 3.3 of\n\"Detection of Stoichiometric Inconsistencies in Biomolecular Models.\"\nBioinformatics 24, no. 19 (2008): 2245.\ndoi: 10.1093/bioinformatics/btn425.","message":null,"data":[["o2_u"],["o2_c"],["o2_cx"],["h2o2_c"],["o2s_c"],["o2_e"],["o2_p"],["photon410_e"],["h_p"],["photon430_e"]],"format_type":"count","metric":10},"test_detect_energy_generating_cycles":{"duration":{"MNXM3":0.15587354600000936,"MNXM63":0.15694774099995357,"MNXM51":0.15586729400001786,"MNXM121":0.15668301400000928,"MNXM423":0.017236948000004304,"MNXM6":0.11340519599997378,"MNXM10":0.11216843500000095,"MNXM38":0.017044714000007843,"MNXM208":0.11115205700002662,"MNXM191":0.013332565999974122,"MNXM223":0.01213471699998081,"MNXM7517":0.012028829000030328,"MNXM12233":0.010772300000041923,"MNXM558":0.011445894999951634,"MNXM21":0.15741060699997433,"MNXM89557":0.15534100200000012},"result":{"MNXM3":"failed","MNXM63":"passed","MNXM51":"passed","MNXM121":"passed","MNXM423":"skipped","MNXM6":"passed","MNXM10":"passed","MNXM38":"skipped","MNXM208":"passed","MNXM191":"skipped","MNXM223":"skipped","MNXM7517":"skipped","MNXM12233":"skipped","MNXM558":"skipped","MNXM21":"passed","MNXM89557":"passed"},"title":"Erroneous Energy-generating Cycles","summary":"When a model is not sufficiently constrained to account for the\nthermodynamics of reactions, flux cycles may form which provide reduced\nmetabolites to the model without requiring nutrient uptake. These cycles\nare referred to as erroneous energy-generating cycles. Their effect on the\npredicted growth rate in FBA may account for an increase of up to 25%,\nwhich makes studies involving the growth rates predicted from such models\nunreliable.\n\nImplementation:\nThis test uses an implementation of the algorithm presented by:\nFritzemeier, C. J., Hartleb, D., Szappanos, B., Papp, B., & Lercher,\nM. J. (2017). Erroneous energy-generating cycles in published genome scale\nmetabolic networks: Identification and removal. PLoS Computational\nBiology, 13(4), 1–14. http://doi.org/10.1371/journal.pcbi.1005494\n\nFirst attempt to identify the main compartment (cytosol), then attempt to\nidentify each metabolite of the referenced list of energy couples via an\ninternal mapping table. Construct a dissipation reaction for each couple.\nCarry out FBA with each dissipation reaction as the objective and report\nthose reactions that non-zero carry flux.","message":{"MNXM3":"The model can produce 'MNXM3' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 545 reactions are involved in\nthose cycles: EX_hco3_e, ADPT, O2tcx, AOXPBDC, DNTPPA, ...","MNXM63":"The model can produce 'MNXM63' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM51":"The model can produce 'MNXM51' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM121":"The model can produce 'MNXM121' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM6":"The model can produce 'MNXM6' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM10":"The model can produce 'MNXM10' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM208":"The model can produce 'MNXM208' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM21":"The model can produce 'MNXM21' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:","MNXM89557":"The model can produce 'MNXM89557' without requiring resources. This is\ncaused by improperly constrained reactions leading to erroneous\nenergy-generating cycles. The following 0 reactions are involved in\nthose cycles:"},"data":{"MNXM3":["EX_hco3_e","ADPT","O2tcx","AOXPBDC","DNTPPA","BIOMASS_PIGMENTS","H2Otu_syn","DTMPK","BIOMASS__1","ORNTA","5DOAN","3HAD160","RNDR3","Htex","HISTDa","TRPS3","DMBZIDS2","HSTPT","ORNDC","U23GAAT2","HOXGfx","PGK","IMPD","LPOR","CHRPL","GCALDDy","MSBENZMT","DESAT18a","FUM","PHYFXOR","TMPPP_1","VPAMTr","RNDR1","GLYCL","ACONT","NDPK7","GTPCI","AIRC2","IGPS","MTAP","DHORD3um","MTHFC","HBZNPT","GCATENEC","HSDy","HISTDb","UPPDC1","GARFT","H4THDPR","UDPG4E","GLCS3","AICART","ASPTA","PRAGSr","SQD1","ACKr","UDCPDPS","GK1","SHKK","G1PACT","3HAD60","PGI","OHPBAT","PQH2tum","O2tu","O2tpp","H2Otex","EX_mg2_e","3HAD80","3OAR160","PPK","GALUi","PHYTES2_1","IGPDH","OMPDC","NADS2","GLUTRR","UAMAGS","ADCL","CYTK1","DAPDC","PSIum","THRS","NAMNPP","FOLD3","P5CR","ICHORS","3OAS140","PPK2","GLYDHDA","SBP","H4THDPS","EAR60y","UAPGR","DHAD1","SUCBZL","ADSL1r","NNATr","PERD","PPBNGS","ADOCBLS","LTHRK","APRAUR","O2tex","ALAALAr","ADCPS2","GF6PTA","DNMPPA","PGMT","G5SADs","LPADSS2","DPR","EAR120y","MAN1PT","TKT2","PSP_L","PPNCL2","CHORS","CS","PPCDC","ADMDC","PPPGO2_1","BIOMASS_DNA","DMATT","G3PD2","BIOMASS_CELL_WALL","PHYTES","RB15BPtcx","MOHMT","FBA","RZ5PP","ASAD","CYSS_2","LYCOPC","ACOTA","3HAD180","ALDD2y","3OAS80","PSCVT","CBPS","MEPCT","PDX5POi","DHAD2","DHFS","PGCD","NNDMBRT","PRATPP","SERAT","PRAIS","PRAMPC","ACBIPGT","SEPHCHCS","ORNTAC","SUCBZS","UHGADA2","DHNANT","GGDPR","ASP1DC","PPNDH","ASPK","DXPS","ME2","3PGtcx","PAPSR","SADT","BIOMASS_COFACTORS","DPCOAK","ARGSL","HSK","MTHFD","PMDPHT","3HAD140","DAPE","BCAROHX2","HPPK","PANTS","AHCi","ALAD_L","GTPCII","GLCBRAN3","DB4PS","DXPRIi","FBA3","RBFSa","GLUTRS","MPOMMM","METAT","EAR160y","DHORTS","PDX5PS2","KARI_23dhmp_1","GAPDi_nadp","AIRC3","UMPK","RBFSb_1","SUCDum","FBP","CITCIb","TMPK","AGPR","CDPMEK","DVOCHR_1","H2CO3_NAt_syn","HEMEOS","PMANM","RPE","MPOMT_1","UAMAS","CYOOum","METS_1","PRUK","FNOR_1","GART","DMTPHT","DDPA","ASPCT","HSERTA","CYRDAAT","MECDPDHf","Htcx","H2Otpp","HISTP","MTHFR3_1","3HAD40_2","BIOMASS_MEM_LIPIDS","HCO3tcx","IMPC","BIOMASS_PROTEIN","LDAPAT","3OAR40_2","RNDR2","GRTT","NPDPS","3OAS100","ADSL2r","MAN6PI","3OAS120","EAR180y","DHQTi","3OAS60","EAR40y","MG2uabcpp","KARA1","TKT1","IPDDI","PKETF","ENO","UAGCVT","PRASCSi","PRFGS","MG2tex","TRDR","GLUPRT","PSERT","GMPS2","RBFK","NTRIRfx","ACS","DHNCOAS","MCOATA","ARGSS","HMBS","PTPATi","PGLYCP","HTHRPDH","UAGAAT2","SHK3Dr","ORPT","PRPPS","CITMS","SPODM","PGAMT","NNDPR","ADSK","MECDPS","FCLT","SHCHCS3","ADCYRS","ATPPRT","DHQS","ANPRT","ADK1","PRAIi","RBPCcx","UPP3S","DHNPA_1","NADK","BIOMASS_RNA","NADTRHD","PGM","FE3abcpp","DM_dialurate_c","USHD2","DHNCOAT","NPHBDC","DM_co_c","HCO3E_1_cx","DESAT16a","UAGDP","BIOMASS_CARB","2PGLYCtcx","FRTT","3OAS180","EAR80y","SK_amylose_c","EAR140y","EX_k_e","DHPPDA","DHFR","BCAROHX","EX_h2o_e","EX_leu__L_e","MPOMC1_1","ERTHMMOR","EX_fe3_e","EX_so4_e","AFAT","G1SAT","UAAGDS","URIDK2r","CHPHYS","EX_na1_e","PHETA1","DMPPS_syn","ANS2","3OAS160","ACHBSb","ADSS","THRPDC","MPOMOR_1","SPMS","EX_h_e","BPNT","ICDHyr","TMDS3","MTRI","CTPS2","FE3tex","AHSERL2_1","PEPC","CHORM","MPML","Nat_Kpp","TPI","E4PD","CPPPGO","PRMICI","CAT","GLUR","OCBT","GLGC","PYK","ALAR","SULR_2","ADCS","UGMDDS","IG3PS","RPI","NAt3pp","GLYCLTDx","FMNRy_1","GHMT2r","PGPP_OLE_PALM","EX_photon410_e","DM_amob_c","ADNK1","OPMEACPD","OPMEACPR","AGPAT160","AGPATACP_HDE_PALM","LEUtex","BTS6","PMEACPE","G3PAT160","GLUDGE_HDE_HDE","G3PAT161","HCO3tex","G3PAT1819Z_1","EPMEACPR","GLUDGE_OLE_HDE","GLUDGE_OLE_PALM","GLUDGE_HDE_PALM","AGPAT161","AGPATACP_OLE_HDE","AGPATACP_OLE_PALM","GLUDGS_OLE_HDE","GLUDGS_OLE_PALM","GLUDGS_HDE_PALM","GLUDGS_HDE_HDE","TYRTRS","SQDGS_PALM_PALM","SO4tex","SQDGS_HDE_PALM","PGPS_OLE_PALM","DGDGS_HDE_PALM","DGDGS_HDE_HDE","DGDGS_OLE_HDE","DGDGS_OLE_PALM","CDPDAGS_OLE_PALM","GLNTRS","METTRS","SERTRS","NAtex","PROTRS","GLYTRS","CYSTRS","ARGTRS","Ktex","TRPTRS","HISTRS","PHETRS","ASNTRS","ASPTRS","DBTS","THRTRS","LEUTRS","ILETRS","LYSTRS","AOXSr2","AMAOTr","LIPOS2","ALATRS","TRNFE","VALTRS","BACCL","LIPOCT","ZXANHX","PHOA410um","PHOA430um","OGMEACPR","PLYCOI","ZCARDS","PHOA650um","PHOA670um","GMAND","GFUCS","ETCHLAS","ETBCARO","COLIPAabcex","AACPS6","ALDR18","ALDDC17","THZT","PHYPQOX","CXANHX","OGMEACPS","A5PISO","KDOPS","KDOPP","NO2tex","KDOCT2","EGMEACPR","DXYTST","UAG2E","OANTS","ACGAMT","Htabcpp","ETAPCPSII","DEXZEAX","ACMAMT","ICLIPAabcpp","ICLIPAS","MOAT_1","MPTG","MPTG2","UAGPT3","GLYCOX1","PAPPT3","OANTIabcpp","OANTILpp","UDCPDP","ETCPC","NO2tabcpp","FALGTHLs","MALCOAMT","MDRPD","PSIICRum","ENOPH","QULNS","ILETA","ARD","VALTA","NDPK3","NDPK1","NDPK8","UNK3","NDPK5","NDPK4","ZISO","NDPK2","3OAR180","3OAR140","PAPA160","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","ACGK","LEUabcpp","ACLSa","SULabcpp","PAPA_OLE_PALM","TYRTA","ACLSb","OPMEACPS","EAR100y","KAS15","FALDH2","KARI_1","3HAD120","OGMEACPD","ACCOAC","ASPO5","PTHPS","CITCIa","3HAD100","PNTK","3OAR120","3OAR60","3OAR100","3OAR80","ALCD1","NDH_1_1_um_copy1","PCHLDA430","SFGTHi","SPR","RNDR4","TRPS2","PSICSum","PPND","CBFCum","THBTGT","THISAT","PSIIum","ATPSum","CYSDES","GLNS","THII","SHS1","PSIICSum","ASNS1","EX_no2_e","MDH","DRBK","DRPA","FA180ACPHi"],"MNXM63":[],"MNXM51":[],"MNXM121":[],"MNXM6":[],"MNXM10":[],"MNXM208":[],"MNXM21":[],"MNXM89557":[]},"format_type":"count","metric":{"MNXM3":0.5364173228346457,"MNXM63":0.0,"MNXM51":0.0,"MNXM121":0.0,"MNXM6":0.0,"MNXM10":0.0,"MNXM208":0.0,"MNXM21":0.0,"MNXM89557":0.0},"score":{"MNXM3":0.4635826771653543,"MNXM63":1.0,"MNXM51":1.0,"MNXM121":1.0,"MNXM6":1.0,"MNXM10":1.0,"MNXM208":1.0,"MNXM21":1.0,"MNXM89557":1.0}},"test_reaction_charge_balance":{"duration":0.0017633790000104455,"result":"failed","title":"Charge Balance","summary":"This will exclude biomass, exchange and demand reactions as they are\nunbalanced by definition. It will also fail all reactions where at\nleast one metabolite does not have a charge defined.\n\nIn steady state, for each metabolite the sum of influx equals the sum\nof efflux. Hence the net charges of both sides of any model reaction have\nto be equal. Reactions where at least one metabolite does not have a\ncharge are not considered to be balanced, even though the remaining\nmetabolites participating in the reaction might be.\n\nImplementation:\nFor each reaction that isn't a boundary or biomass reaction check if each\nmetabolite has a non-zero charge attribute and if so calculate if the\noverall sum of charges of reactants and products is equal to zero.","message":"A total of 40 (4.83%) reactions are charge unbalanced with at\nleast one of the metabolites not having a charge or the overall\ncharge not equal to 0: MPTS, PSIum, FA80ACPHi, CYOOum, FACOAE100, ...","data":["MPTS","PSIum","FA80ACPHi","CYOOum","FACOAE100","RBPCcx","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","CPMPS","FACOAL181i","GTPC","FACOAL80i","FNOR","PC6YM","FACOAE80","FACOAE160","DRBK","MOGDS","FACOAL100i","FACOAL120i","DPGM","FACOAE180","DRPA","FACOAE181","GUACYC","RDXRr","FA100ACPHi","OANTS","PSIIum","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA181ACPHi","FACOAE120","FACOAE140","ICLIPAS","FACOAE161"],"format_type":"count","metric":0.04825090470446321},"test_reaction_mass_balance":{"duration":0.029734163000000535,"result":"failed","title":"Mass Balance","summary":"This will exclude biomass, exchange and demand reactions as they are\nunbalanced by definition. It will also fail all reactions where at\nleast one metabolite does not have a formula defined.\n\nIn steady state, for each metabolite the sum of influx equals the sum\nof efflux. Hence the net masses of both sides of any model reaction have\nto be equal. Reactions where at least one metabolite does not have a\nformula are not considered to be balanced, even though the remaining\nmetabolites participating in the reaction might be.\n\nImplementation:\nFor each reaction that isn't a boundary or biomass reaction check if each\nmetabolite has a non-zero elements attribute and if so calculate if the\noverall element balance of reactants and products is equal to zero.","message":"A total of 38 (4.58%) reactions are mass unbalanced with at least\none of the metabolites not having a formula or the overall mass not\nequal to 0: MPTS, OANTIabcpp, OANTILpp, STACPSI, CYOOum, ...","data":["MPTS","OANTIabcpp","OANTILpp","STACPSI","CYOOum","PHOA430um","SUCRt2","RBPCcx","MOCOS","MOADSUx","PHOA410um","MPTAT","MPTSS","CPMPS","FACOAL181i","GTPC","PHOA490um","FNOR","PC6YM","PHOA450um","PHOA470um","PHOA510um","MOGDS","FACOAE181","ETAPCPSII","OANTS","PSIIum","STCHLPSIum","PCHLDA650","FA180ACPHi","FA181ACPHi","PHOA690um","ICLIPAabcpp","COLIPAabcex","ETBCARO","ICLIPAS","ETCHLAS","PCHLDA430"],"format_type":"count","metric":0.045838359469240045},"test_blocked_reactions":{"duration":1.2424536030000013,"result":"failed","title":"Universally Blocked Reactions","summary":"Universally blocked reactions are reactions that during Flux Variability\nAnalysis cannot carry any flux while all model boundaries are open.\nGenerally blocked reactions are caused by network gaps, which can be\nattributed to scope or knowledge gaps.\n\nImplementation:\nUse flux variability analysis (FVA) implemented in\ncobra.flux_analysis.find_blocked_reactions with open_exchanges=True.\nPlease refer to the cobrapy documentation for more information:\nhttps://cobrapy.readthedocs.io/en/stable/autoapi/cobra/flux_analysis/\nvariability/index.html#cobra.flux_analysis.variability.\nfind_blocked_reactions","message":"There are 229 (22.56%) blocked reactions in         the model:\nEX_mn2_e, HEMEAS_1, GLYOX, NMNS, G1PTT, ...","data":["EX_mn2_e","HEMEAS_1","GLYOX","NMNS","G1PTT","ZNabcpp","DNAMTn2r","MI3PP","PROAKGOX1","NTD6","G1PCTYT","DDPGA","DPOR","ARGOXRum","MNabc_1","CPPPGO2","EX_ca2_e","GLYALDDy","HPROb","NI2uabcpp","TDPDRR","TDPGDH","TDPDRE","SPRMS","CUabcpp","TRSARyr","MOBDabcpp","EX_fe2_e","PQH2tcm","EX_cu2_e","SK_14glucan_c","SK_glycogen_c","EX_zn2_e","EX_mobd_e","DADK","EX_ni2_e","ARGDHpp","GLYOX_1","FE2tex","NI2tex","MNtex","CU2tex","H2Otcx","Zn2tex","QUERT","MOBDtex","CA2tex","UDPGLDC","CHLADMT_1","FMETTRS","BTNPL2","LIPAMPL_1","LIPATPT_1","CPH4S","CDGS","CCGS","CDGR","SAMTRI","EPXQR","UPPRT","UDPGD","MLDCP1App","CDPGLC46DH","ALCD19","MLDCP1Bpp","MLDCP2App","MLDCP2Bpp","PFOR","MLTGY2pp","MLTGY3pp","CLtex","EX_cl_e","AGM3PApp","CELLSYN","ALAALAabcpp","PHEOASE","MCTP1Bpp","PHEOX_1","EHGLAT","PHYTK","NDH_1_4_um_copy2","AMANAPEr","CLt3_1pp","Ktu","NDH_1_1_um_copy2","MDDCP5pp","MDDEP2pp","EX_tre_e","EX_man_e","EX_galt_e","EX_arab__L_e","EX_acgam_e","EX_glcr_e","EX_succ_e","EX_gal_e","EX_asp__L_e","EX_pro__L_e","EX_ala__D_e","EX_ser__D_e","EX_for_e","EX_mnl_e","EX_glu__L_e","EX_sbt__D_e","EX_glyc_e","EX_fuc__L_e","EX_glcur_e","EX_glcn_e","EX_glyc3p_e","EX_xyl__D_e","EX_lac__L_e","EX_g6p_e","EX_malt_e","EX_melib_e","EX_thymd_e","EX_galctn__D_e","EX_rib__D_e","EX_rmn_e","EX_fru_e","EX_ac_e","EX_glc__D_e","EX_asn__L_e","EX_uri_e","EX_12ppd__S_e","EX_akg_e","EX_lcts_e","EX_malttr_e","EX_dad_2_e","EX_adn_e","EX_g1p_e","EX_f6p_e","EX_ins_e","EX_cit_e","EX_inost_e","EX_fum_e","EX_ppa_e","EX_galct__D_e","EX_glyclt_e","EX_mal__D_e","EX_mal__L_e","EX_ser__L_e","EX_thr__L_e","EX_ala__L_e","EX_acac_e","EX_acmana_e","EX_galur_e","EX_peamn_e","EX_etha_e","EX_tym_e","EX_lyx__L_e","EX_pyr_e","EX_galctn__L_e","EX_acnam_e","EX_all__D_e","EX_4abut_e","EX_but_e","EX_dca_e","EX_5dglcn_e","EX_hxa_e","EX_tartr__L_e","EX_lys__L_e","EX_met__L_e","EX_gly_e","EX_his__L_e","EX_hom__L_e","EX_ile__L_e","EX_orn_e","EX_phe__L_e","EX_val__L_e","EX_dha_e","EX_cys__L_e","EX_urea_e","EX_trp__L_e","EX_tyr__L_e","EX_agm_e","EX_acgal_e","EX_gam_e","EX_ura_e","EX_ade_e","EX_cytd_e","EX_csn_e","EX_gua_e","EX_gsn_e","EX_thym_e","EX_xan_e","EX_xtsn_e","EX_alltn_e","EX_23camp_e","EX_3amp_e","EX_gmp_e","EX_23cgmp_e","EX_3gmp_e","EX_cmp_e","EX_23ccmp_e","EX_gam6p_e","EX_3cmp_e","EX_ump_e","EX_23cump_e","EX_man6p_e","EX_pser__L_e","EX_thrp_e","EX_3ump_e","EX_tyrp_e","EX_minohp_e","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","FNOR","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA181ACPHi","FA80ACPHi","GLCP4","GLCP3"],"format_type":"count","metric":0.22561576354679802},"test_find_stoichiometrically_balanced_cycles":{"duration":2.411515759999986,"result":"failed","title":"Stoichiometrically Balanced Cycles","summary":"Stoichiometrically Balanced Cycles are artifacts of insufficiently\nconstrained networks resulting in reactions that can carry flux when\nall the boundaries have been closed.\n\nImplementation:\nClose all model boundary reactions and then use flux variability analysis\n(FVA) to identify reactions that carry flux.","message":"There are 10 (0.99%) reactions         which participate in SBC in the\nmodel: GLCS3, PPK, GLYDHDA, GLCP2_1, ALAD_L, ...","data":["GLCS3","PPK","GLYDHDA","GLCP2_1","ALAD_L","GAPDi_nadp","NADTRHD","GAPD","GLGC","AGTi"],"format_type":"count","metric":0.009852216748768473},"test_find_orphans":{"duration":0.009689333999972405,"result":"failed","title":"Orphan Metabolites","summary":"Orphans are metabolites that are only consumed but not produced by\nreactions in the model. They may indicate the presence of network and\nknowledge gaps.\n\nImplementation:\nFind orphan metabolites structurally by considering only reaction\nequations and bounds. FBA is not carried out.","message":"A total of 13 (1.41%) metabolites are not produced by any reaction\nof the model: 2h3oppan_c, mi3p__D_c, 1p3h5c_c, dna_c, accp_c, ...","data":["2h3oppan_c","mi3p__D_c","1p3h5c_c","dna_c","accp_c","lipoate_c","fldox_c","cl_c","acmama_c","csn_c","cyst-L_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.01406926406926407},"test_find_deadends":{"duration":0.00757055699995135,"result":"failed","title":"Dead-end Metabolites","summary":"Dead-ends are metabolites that can only be produced but not consumed by\nreactions in the model. They may indicate the presence of network and\nknowledge gaps.\n\nImplementation:\nFind dead-end metabolites structurally by considering only reaction\nequations and bounds. FBA is not carried out.","message":"A total of 27 (2.92%) metabolites are not consumed by any reaction\nof the model: mn2_c, sprm_c, 5g2oxpt_c, inost_c, ni2_c, ...","data":["mn2_c","sprm_c","5g2oxpt_c","inost_c","ni2_c","dtdprmn_c","4hpro_LT_c","cdp4dh6doglc_c","dna5mtc_c","rcc_c","btnCCP_c","murein5px3p_p","quetrna_c","udpxyl_c","LalaDgluMdap_p","fldrd_c","5g2oxpt_p","fmettrna_c","h2o2_p","b14glucan_c","iscs_c","38ch2gtp_c","fdxo_2_2_c","mocogdp_c","acmam_c","g15lac_c","35cgmp_c"],"format_type":"count","metric":0.02922077922077922},"test_find_disconnected":{"duration":0.0005049769999914133,"result":"passed","title":"Metabolite Connectivity","summary":"Disconnected metabolites are not part of any reaction in the model. They\nare most likely left-over from the reconstruction process, but may also\npoint to network and knowledge gaps.\n\nImplementation:\nCheck for any metabolites of the cobra.Model object with emtpy reaction\nattribute.","message":"A total of 0 (0.00%) metabolites are not associated with any\nreaction of the model:","data":[],"format_type":"count","metric":0.0},"test_find_metabolites_not_produced_with_open_bounds":{"duration":42.82381452300001,"result":"failed","title":"Metabolite Production In Complete Medium","summary":"In complete medium, a model should be able to divert flux to every\nmetabolite. This test opens all the boundary reactions i.e. simulates a\ncomplete medium and checks if any metabolite cannot be produced\nindividually using flux balance analysis. Metabolites that cannot be\nproduced this way are likely orphan metabolites, downstream of reactions\nwith fixed constraints, or blocked by a cofactor imbalance. To pass this\ntest all metabolites should be producible.\n\nImplementation:\nOpen all model boundary reactions, then for each metabolite in the model\nadd a boundary reaction and maximize it with FBA.","message":"A total of 147 (15.91%) metabolites cannot be produced in complete\nmedium: 1p3h5c_c, 2h3oppan_c, 3hbutACP_c, 3hddecACP_c, 3hdecACP_c, ...","data":["1p3h5c_c","2h3oppan_c","3hbutACP_c","3hddecACP_c","3hdecACP_c","3hhexACP_c","3hmrsACP_c","3hoctACP_c","3hoctaACP_c","3hpalmACP_c","3oddecACP_c","3odecACP_c","3ohexACP_c","3omrsACP_c","3ooctACP_c","3ooctdACP_c","3opalmACP_c","4h2oglt_c","5g2oxpt_p","ACP_c","acACP_c","accp_c","acmam_c","acmama_c","actACP_c","alaala_p","alatrna_c","allocy_c","allocy_exc_c","argtrna_c","asntrna_c","asptrna_c","athis_c","bglyg4n_c","btnCCP_c","but2eACP_c","butACP_c","cl_c","csn_c","cyst-L_c","cystrna_c","dcaACP_c","ddcaACP_c","dna5mtc_c","dna_c","e4hglu_c","egmeACP_c","epmeACP_c","fdxo_2_2_c","fdxox_c","fdxrd_c","fldox_c","fldrd_c","fmettrna_c","gcaro_c","glntrna_c","glutrna_c","glyg4n_c","glytrna_c","gmeACP_c","h2o2_p","hdeACP_c","hexACP_c","hgmeACP_c","histrna_c","hpmeACP_c","iletrna_c","inost_c","iscs_c","iscsh_c","iscssh_c","leutrna_c","lgt__S_c","lipamp_c","lipoate_c","lyc_c","lystrna_c","malACP_c","mettrna_c","mi3p__D_c","moadamp_c","moadcoo_c","moadcosh_c","moco_c","mocogdp_c","mpt_c","mptamp_c","mthgxl_c","myrsACP_c","ocACP_c","ocdcaACP_c","octe9ACP_c","ogmeACP_c","opmeACP_c","p680_exc_um","p680_um","p700_exc_um","p700_um","palmACP_c","pcox_u","pcrd_u","phetrna_c","phytol_c","pimACP_c","pmeACP_c","protrna_c","ps2d1_exc_um","ps2d1_um","rdxo_c","rdxr_c","sertrna_c","tddec2eACP_c","tdec2eACP_c","thex2eACP_c","this_c","thissh_c","thrtrna_c","tmrs2eACP_c","toct2eACP_c","toctd2eACP_c","tpalm2eACP_c","trdox_c","trdrd_c","trnaala_c","trnaarg_c","trnaasn_c","trnaasp_c","trnacys_c","trnagln_c","trnaglu_c","trnagly_c","trnahis_c","trnaile_c","trnaleu_c","trnalys_c","trnamet_c","trnaphe_c","trnapro_c","trnaser_c","trnathr_c","trnatrp_c","trnatyr_c","trnaval_c","trptrna_c","tyrtrna_c","ura_c","valtrna_c"],"format_type":"count","metric":0.1590909090909091},"test_find_metabolites_not_consumed_with_open_bounds":{"duration":42.769766049,"result":"failed","title":"Metabolite Consumption In Complete Medium","summary":"In complete medium, a model should be able to divert flux from every\nmetabolite. This test opens all the boundary reactions i.e. simulates a\ncomplete medium and checks if any metabolite cannot be consumed\nindividually using flux balance analysis. Metabolites that cannot be\nconsumed this way are likely dead-end metabolites or upstream of reactions\nwith fixed constraints. To pass this test all metabolites should be\nconsumable.\n\nImplementation:\nOpen all model boundary reactions, then for each metabolite in the model\nadd a boundary reaction and minimize it with FBA.","message":"A total of 186 (20.13%) metabolites cannot be consumed in complete\nmedium: 1p3h5c_c, 35cgmp_c, 38ch2gtp_c, 3hbutACP_c, 3hddecACP_c, ...","data":["1p3h5c_c","35cgmp_c","38ch2gtp_c","3hbutACP_c","3hddecACP_c","3hdecACP_c","3hhexACP_c","3hmrsACP_c","3hoctACP_c","3hoctaACP_c","3hpalmACP_c","3oddecACP_c","3odecACP_c","3ohexACP_c","3omrsACP_c","3ooctACP_c","3ooctdACP_c","3opalmACP_c","4hpro_LT_c","5g2oxpt_c","5g2oxpt_p","ACP_c","LalaDgluMdap_p","acACP_c","accp_c","acmam_c","acmama_c","actACP_c","alatrna_c","allocy_c","allocy_exc_c","anhgm3p_p","argtrna_c","asntrna_c","asptrna_c","athis_c","b14glucan_c","btnCCP_c","but2eACP_c","butACP_c","cdg_c","cdp4dh6doglc_c","cdpglc_c","cph4_c","cpmp_c","cu2_c","cystrna_c","dcaACP_c","dca_c","dcacoa_c","ddcaACP_c","ddca_c","ddcacoa_c","dna5mtc_c","dna_c","dtdp4d6dg_c","dtdp4d6dm_c","dtdpglu_c","dtdprmn_c","egmeACP_c","epmeACP_c","epxqtrna_c","fdxo_2_2_c","fdxox_c","fdxrd_c","fldox_c","fldrd_c","fmettrna_c","g15lac_c","gcaro_c","glntrna_c","glutrna_c","glytrna_c","gmeACP_c","h2o2_p","hdca_c","hdcea_c","hdcoa_c","hdeACP_c","hexACP_c","hgmeACP_c","histrna_c","hpmeACP_c","iletrna_c","imgly_c","inost_c","iscs_c","iscsh_c","iscssh_c","leutrna_c","lyc_c","lystrna_c","malACP_c","mettrna_c","mi3p__D_c","mn2_c","moadamp_c","moadcoo_c","moadcosh_c","mobd_c","moco_c","mocogdp_c","mpt_c","mptamp_c","murein3p3p_p","murein3px4p_p","murein4p3p_p","murein5p3p_p","murein5px3p_p","myrsACP_c","ni2_c","ocACP_c","occoa_c","ocdcaACP_c","octa_c","octe9ACP_c","octe9_c","octe9coa_c","ogmeACP_c","opmeACP_c","p680_exc_um","p680_um","p700_exc_um","p700_um","palmACP_c","pcox_u","pcrd_u","phetrna_c","phphbda_c","phptna_c","pimACP_c","pmeACP_c","pmtcoa_c","pq_cm","pqh2_cm","preq0_c","preq1_c","preqtrna_c","protrna_c","ps2d1_exc_um","ps2d1_um","quetrna_c","rcc_c","rdxo_c","rdxr_c","sertrna_c","sprm_c","tdcoa_c","tddec2eACP_c","tdec2eACP_c","thex2eACP_c","this_c","thissh_c","thrtrna_c","tmrs2eACP_c","toct2eACP_c","toctd2eACP_c","tpalm2eACP_c","trdox_c","trdrd_c","trnaala_c","trnaarg_c","trnaasn_c","trnaasp_c","trnacys_c","trnagln_c","trnaglu_c","trnagly_c","trnahis_c","trnaile_c","trnaleu_c","trnalys_c","trnamet_c","trnaphe_c","trnapro_c","trnaser_c","trnathr_c","trnatrp_c","trnatyr_c","trnaval_c","trptrna_c","ttdca_c","tyrtrna_c","udpglcur_c","udpxyl_c","valtrna_c"],"format_type":"count","metric":0.2012987012987013},"test_find_reactions_unbounded_flux_default_condition":{"duration":2.266391265999971,"result":"failed","title":"Unbounded Flux In Default Medium","summary":"A large fraction of model reactions able to carry unlimited flux under\ndefault conditions indicates problems with reaction directionality,\nmissing cofactors, incorrectly defined transport reactions and more.\n\nImplementation:\nWithout changing the default constraints run flux variability analysis.\nFrom the FVA results identify those reactions that carry flux equal to the\nmodel's maximal or minimal flux.","message":" A fraction of 12.06% of the non-blocked reactions (in total 92\nreactions) can carry unbounded flux in the default model\ncondition. Unbounded reactions may be involved in\nthermodynamically infeasible cycles: ATPM, PGK, VPAMTr, GLCS3, PPK,\n...","data":["ATPM","PGK","VPAMTr","GLCS3","PPK","PSIum","PFK_3","GLYDHDA","SBP","ALAALAr","PGMT","GLYCK","PSP_L","HPYRRy","FBA","PGCD","CA2abcpp","3PGtcx","ALAD_L","FBA3","GAPDi_nadp","NTD7","FBP","BPNT2","PSERT","SPTc","ADSK","PPA","ADK1","NADTRHD","PFK","GLGC","PYK","CA2t2pp","EX_photon410_e","EX_photon430_e","EX_photon450_e","EX_photon470_e","EX_photon490_e","EX_photon510_e","ADNK1","EX_photon530_e","EX_photon550_e","EX_photon570_e","EX_photon590_e","EX_photon610_e","EX_photon630_e","EX_photon650_e","EX_photon670_e","EX_photon690_e","DAGK160","DAGK_HDE_PALM","DAGK161","AGTi","PHOA410um","PHOA430um","PHOA450um","PHOA470um","PHOA490um","PHOA510um","PHOA530um","PHOA550um","PHOA570um","PHOA590um","PHOA610um","PHOA630um","PHOA650um","PHOA670um","PHOA690um","DM_pho_loss_c","ETCHLAS","ETBCARO","Htabcpp","ETAPCPSII","STACPSI","ETCPC","PSICRum","NDPK1","ALAALAD","NDPK2","PAPA160","PAPA_HDE_PALM","PAPA161","PAPA_OLE_HDE","PAPA_OLE_PALM","DAGK_OLE_HDE","DAGK_OLE_PALM","PSICSum","CBFCum","PCXHtpp","GLNS","PSIICSum"],"format_type":"percent","metric":0.12057667103538663},"test_gene_essentiality_from_data_qualitative":{"duration":{"knockouts":2.904603064000014},"result":{"knockouts":"failed"},"title":"Gene Essentiality Prediction","summary":"The in-silico gene essentiality is compared with experimental\ndata and the accuracy is expected to be better than 0.95.\nIn principal, Matthews' correlation coefficient is a more comprehensive\nmetric but is a little fragile to not having any false negatives or false\npositives in the output.\n\nImplementation:\nRead and validate experimental config file and data tables. Constrain the\nmodel with the parameters provided by a user's definition of the medium,\nthen compute a confusion matrix based on the predicted essential, expected\nessential, predicted nonessential and expected nonessential genes.\nThe individual values of the confusion matrix are calculated as described\nin https://en.wikipedia.org/wiki/Confusion_matrix","message":{"knockouts":"Ideally, every model would show a perfect accuracy of 1. In\nname 'knockouts' the model has  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Prediction","summary":"The in-silico growth prediction is compared with experimental\ndata and the accuracy is expected to be better than 0.95.\nIn principal, Matthews' correlation coefficient is a more comprehensive\nmetric but is a little fragile to not having any false negatives or false\npositives in the output.\n\nImplementation:\nRead and validate experimental config file and data tables. Constrain the\nmodel with the parameters provided by a user's definition of the medium,\nthen compute a confusion matrix based on the predicted true, expected\ntrue, predicted false and expected false growth.\nThe individual values of the confusion matrix are calculated as described\nin https://en.wikipedia.org/wiki/Confusion_matrix","message":{},"data":{},"format_type":"percent","metric":{},"score":{}},"test_absolute_extreme_coefficient_ratio":{"duration":0.0071756049999862626,"result":"passed","title":"Ratio Min/Max Non-Zero Coefficients","summary":"This test will return the absolute largest and smallest, non-zero\ncoefficients of the stoichiometric matrix. A large ratio of these values\nmay point to potential numerical issues when trying to solve different\nmathematical optimization problems such as flux-balance analysis.\n\nTo pass this test the ratio should not exceed 10^9. This threshold has\nbeen selected based on experience, and is likely to be adapted when more\ndata on solver performance becomes available.\n\nImplementation:\nCompose the stoichiometric matrix, then calculate absolute coefficients and\nlastly use the maximal value and minimal non-zero value to calculate the\nratio.","message":"The ratio of the absolute values of the largest coefficient 1080.0 and\nthe lowest, non-zero coefficient 0.0001 is: 1.08E+07.","data":10800000.0,"format_type":"percent","metric":0.0},"test_number_independent_conservation_relations":{"duration":0.23767092899998943,"result":"passed","title":"Independent Conservation Relations","summary":"This test will return the number of conservation relations, i.e.,\nconservation pools through the left null space of the stoichiometric\nmatrix. This test is not scored, as the dimension of the left null space\nis system-specific.\n\nImplementation:\nCalculate the left null space, i.e., the null space of the transposed\nstoichiometric matrix, using an algorithm based on the singular value\ndecomposition adapted from\nhttps://scipy.github.io/old-wiki/pages/Cookbook/RankNullspace.html\nThen, return the estimated dimension of that null space.","message":"The number of independent conservation relations is 36.","data":36,"format_type":"raw","metric":0.03896103896103896},"test_matrix_rank":{"duration":0.12030225500001279,"result":"passed","title":"Rank","summary":"The rank of the stoichiometric matrix is system specific. It is\ncalculated using singular value decomposition (SVD).\n\nImplementation:\nCompose the stoichiometric matrix, then estimate the rank, i.e. the\ndimension of the column space, of a matrix. The algorithm used by this\nfunction is based on the singular value decomposition of the matrix.","message":"The rank of the S-Matrix is 885.","data":885,"format_type":"raw","metric":0.8719211822660099},"test_degrees_of_freedom":{"duration":0.12671223400002418,"result":"passed","title":"Degrees Of Freedom","summary":"The degrees of freedom of the stoichiometric matrix, i.e., the number\nof 'free variables' is system specific and corresponds to the dimension\nof the (right) null space of the matrix.\n\nImplementation:\nCompose the stoichiometric matrix, then calculate the dimensionality of the\nnull space using the rank-nullity theorem outlined by\nAlama, J. The Rank+Nullity Theorem. Formalized Mathematics 15, (2007).","message":"The degrees of freedom of the S-Matrix are 130.","data":130,"format_type":"raw","metric":0.12807881773399016},"test_sbml_level":{"duration":0.00024009999998497733,"result":"passed","title":"SBML Level and Version","summary":"This test reports if the model file is represented in the latest edition\n(level) of the Systems Biology Markup Language (SBML) which is Level 3,\nand at least version 1.\n\nImplementation:\nThe level and version are parsed directly from the SBML document.","message":"The SBML file uses: SBML Level 3 Version 1","data":"SBML Level 3 Version 1","format_type":"raw","metric":0.0},"test_fbc_presence":{"duration":0.00023215499999196254,"result":"passed","title":"FBC enabled","summary":"The Flux Balance Constraints (FBC) Package extends SBML with structured\nand semantic descriptions for domain-specific model components such as\nflux bounds, multiple linear objective functions, gene-protein-reaction\nassociations, metabolite chemical formulas, charge and related annotations\nwhich are relevant for parameterized GEMs and FBA models. The SBML and\nconstraint-based modeling communities collaboratively develop this package\nand update it based on user input.\n\nImplementation:\nParse the state of the FBC plugin from the SBML document.","message":"The FBC package *is* used.","data":true,"format_type":"raw","metric":0.0},"test_metabolite_sbo_presence":{"duration":0.002271588999974483,"result":"failed","title":"Metabolite General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Implementation:\n    Check if each cobra.Metabolite has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 156 metabolites (16.88%) lack annotation with any type\nof SBO term: tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","data":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.16883116883116883},"test_reaction_sbo_presence":{"duration":0.0025465950000125304,"result":"failed","title":"Reaction General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Implementation:\n    Check if each cobra.Reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 48 reactions (4.73%) lack annotation with any type\nof SBO term: SUCRt2, MOADSUx, MPTS, MOCOS, MPTAT, ...","data":["SUCRt2","MOADSUx","MPTS","MOCOS","MPTAT","MPTSS","CPMPS","GTPC","MDH","FNOR","PC6YM","LYCBC1","MOGDS","AMAA","CSND","CYSTL","DPGM","DRBK","DRPA","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAE180","FACOAE181","FACOAE80","FACOAL100i","FACOAL120i","FACOAL140i","FACOAL160i","FACOAL161i","FACOAL180i","FACOAL181i","FACOAL80i","GLCP4","GLCP3"],"format_type":"count","metric":0.04729064039408867},"test_gene_sbo_presence":{"duration":0.0017907669999885911,"result":"failed","title":"Gene General SBO Presence","summary":"    The Systems Biology Ontology (SBO) allows researchers to annotate a model\n    with terms which indicate the intended function of its individual\n    components. The available terms are controlled and relational and can be\n    viewed here http://www.ebi.ac.uk/sbo/main/tree.\n\n    Check if each cobra.Gene has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\".","message":"A total of 97 genes (11.00%) lack annotation with any type of\nSBO term: cscB, Synpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211,\nSynpcc7942_1656, ...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_metabolic_reaction_specific_sbo_presence":{"duration":0.0012248769999700926,"result":"failed","title":"Metabolic Reaction SBO:0000176 Presence","summary":"    SBO:0000176 represents the term 'biochemical reaction'. Every metabolic\n    reaction that is not a transport or boundary reaction should be annotated\n    with this. The results shown are relative to the total amount of pure\n    metabolic reactions.\n\n    Implementation:\n    Check if each pure metabolic reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being the SBO term above.","message":"A total of 47 metabolic reactions (6.66% of all purely\nmetabolic reactions) lack annotation with the SBO term\n\"SBO:0000176\" for 'biochemical reaction': MOCOS, MOADSUx, FACOAL140i,\nFACOAL160i, MPTAT, ...","data":["MOCOS","MOADSUx","FACOAL140i","FACOAL160i","MPTAT","FACOAL161i","MPTSS","FACOAL180i","CPMPS","FACOAL181i","GTPC","MDH","FACOAL80i","FNOR","GLCP4","PC6YM","GLCP3","CYSTL","FACOAE80","LYCBC1","DRBK","AMAA","MOGDS","CSND","FACOAL100i","DPGM","FACOAE180","DRPA","FACOAE181","G1Dx","GUACYC","RDXRr","FA100ACPHi","FA120ACPHi","FA140ACPHi","FA160ACPHi","FA161ACPHi","FA180ACPHi","FA181ACPHi","FA80ACPHi","FACOAE100","FACOAE120","FACOAE140","FACOAE160","FACOAE161","FACOAL120i","MPTS"],"format_type":"count","metric":0.06657223796033994},"test_transport_reaction_specific_sbo_presence":{"duration":0.0007386650000285044,"result":"failed","title":"Transport Reaction SBO:0000185 Presence","summary":"    'SBO:0000185', 'SBO:0000588', 'SBO:0000587', 'SBO:0000655', 'SBO:0000654',\n    'SBO:0000660', 'SBO:0000659', 'SBO:0000657', and 'SBO:0000658' represent\n    the terms 'transport reaction' and 'translocation reaction', in addition\n    to their children (more specific transport reaction labels). Every\n    transport reaction that is not a pure metabolic or boundary reaction should\n    be annotated with one of these terms. The results shown are relative to the\n    total of all transport reactions.\n\n    Implementation:\n    Check if each transport reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 1 metabolic reactions (0.81% of all transport\nreactions) lack annotation with one of the SBO terms: ['SBO:0000185',\n'SBO:0000588', 'SBO:0000587', 'SBO:0000655', 'SBO:0000654',\n'SBO:0000660', 'SBO:0000659', 'SBO:0000657', 'SBO:0000658'] for\n'biochemical reaction': SUCRt2","data":["SUCRt2"],"format_type":"count","metric":0.008130081300813009},"test_metabolite_specific_sbo_presence":{"duration":0.0021424880000040503,"result":"failed","title":"Metabolite SBO:0000247 Presence","summary":"    SBO:0000247 represents the term 'simple chemical'. Every metabolite should\n    be annotated with this.\n\n    Implementation:\n    Check if each cobra.Metabolite has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 156 transport reactions (16.88% of all metabolites)\nlack annotation with the SBO term \"SBO:0000247\" for\n'simple chemical': tre_e, man_e, galt_e, arab__L_e, acgam_e, ...","data":["tre_e","man_e","galt_e","arab__L_e","acgam_e","glcr_e","succ_e","gal_e","asp__L_e","pro__L_e","ala__D_e","ser__D_e","for_e","mnl_e","glu__L_e","sbt__D_e","glyc_e","fuc__L_e","glcur_e","glcn_e","glyc3p_e","xyl__D_e","lac__L_e","g6p_e","malt_e","melib_e","thymd_e","galctn__D_e","rib__D_e","rmn_e","fru_e","ac_e","glc__D_e","asn__L_e","sucr_e","uri_e","12ppd__S_e","akg_e","lcts_e","malttr_e","dad_2_e","adn_e","g1p_e","f6p_e","ins_e","cit_e","inost_e","fum_e","ppa_e","galct__D_e","glyclt_e","mal__D_e","mal__L_e","ser__L_e","thr__L_e","ala__L_e","acac_e","acmana_e","galur_e","peamn_e","etha_e","tym_e","lyx__L_e","pyr_e","galctn__L_e","acnam_e","all__D_e","4abut_e","but_e","dca_e","5dglcn_e","hxa_e","tartr__L_e","lys__L_e","met__L_e","gly_e","hom__L_e","ile__L_e","orn_e","phe__L_e","val__L_e","dha_e","cys__L_e","urea_e","trp__L_e","tyr__L_e","agm_e","acgal_e","gam_e","ura_e","ade_e","cytd_e","csn_e","gua_e","gsn_e","thym_e","xan_e","xtsn_e","alltn_e","23camp_e","3amp_e","gmp_e","23cgmp_e","3gmp_e","cmp_e","23ccmp_e","gam6p_e","3cmp_e","ump_e","23cump_e","man6p_e","pser__L_e","thrp_e","3ump_e","tyrp_e","minohp_e","iscs_c","moadamp_c","moadcosh_c","cpmp_c","moadcoo_c","mpt_c","moco_c","mptamp_c","38ch2gtp_c","fdxo_2_2_c","gcaro_c","lyc_c","mocogdp_c","acmama_c","acmam_c","csn_c","cyst-L_c","23dpg_c","2dr5p_c","g15lac_c","35cgmp_c","rdxo_c","rdxr_c","dca_c","ddca_c","ttdca_c","hdca_c","hdcea_c","octe9_c","octa_c","dcacoa_c","ddcacoa_c","tdcoa_c","pmtcoa_c","hdcoa_c","stcoa_c","octe9coa_c","occoa_c","bglyg4n_c","glyg4n_c"],"format_type":"count","metric":0.16883116883116883},"test_gene_specific_sbo_presence":{"duration":0.0018959450000011202,"result":"failed","title":"Gene SBO:0000243 Presence","summary":"    SBO:0000243 represents the term 'gene'. Every gene should\n    be annotated with this.\n\n    Implementation:\n    Check if each cobra.Gene has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 97 genes (11.00% of all genes) lack             annotation\nwith the SBO term \"SBO:0000243\" for             'gene': cscB,\nSynpcc7942_2062, Synpcc7942_1189, Synpcc7942_1211, Synpcc7942_1656,\n...","data":["cscB","Synpcc7942_2062","Synpcc7942_1189","Synpcc7942_1211","Synpcc7942_1656","Synpcc7942_B2620","Synpcc7942_1051","Synpcc7942_2542","Synpcc7942_1232","Synpcc7942_2332","Synpcc7942_1048","Synpcc7942_1088","Synpcc7942_0239","Synpcc7942_1054","Synpcc7942_2158","Synpcc7942_0327","Synpcc7942_1055","Synpcc7942_0328","Synpcc7942_1479","Synpcc7942_1053","Synpcc7942_1052","Synpcc7942_0322","Synpcc7942_2331","Synpcc7942_0475","Synpcc7942_2030","Synpcc7942_1630","Synpcc7942_1049","Synpcc7942_0325","Synpcc7942_0326","Synpcc7942_1050","Synpcc7942_0323","Synpcc7942_2426","Synpcc7942_0511","Synpcc7942_1231","Synpcc7942_1047","Synpcc7942_0113","Synpcc7942_0202","Synpcc7942_2603","Synpcc7942_2604","Synpcc7942_0201","Synpcc7942_2602","Synpcc7942_1408","Synpcc7942_1407","Synpcc7942_2175","Synpcc7942_1409","Synpcc7942_1406","Synpcc7942_1541","Synpcc7942_2581","Synpcc7942_0338","Synpcc7942_0978","Synpcc7942_0698","Synpcc7942_1749","Synpcc7942_0814","Synpcc7942_0898","Synpcc7942_1499","Synpcc7942_0508","Synpcc7942_0385","Synpcc7942_0357","Synpcc7942_1475","Synpcc7942_1447","Synpcc7942_1423","Synpcc7942_1388","Synpcc7942_B2619","Synpcc7942_0932","Synpcc7942_1378","Synpcc7942_0652","Synpcc7942_0888","Synpcc7942_0498","Synpcc7942_1973","Synpcc7942_1608","Synpcc7942_1763","Synpcc7942_2582","Synpcc7942_2588","Synpcc7942_2055","Synpcc7942_0135","Synpcc7942_1910","Synpcc7942_1493","Synpcc7942_1266","Synpcc7942_0706","Synpcc7942_1850","Synpcc7942_0693","Synpcc7942_2613","Synpcc7942_1450","Synpcc7942_2442","Synpcc7942_2443","Synpcc7942_2445","Synpcc7942_2444","Synpcc7942_2441","Synpcc7942_0973","Synpcc7942_0974","Synpcc7942_1319","Synpcc7942_1715","Synpcc7942_B2633","Synpcc7942_0485","Synpcc7942_0469","Synpcc7942_1516","Synpcc7942_2078"],"format_type":"count","metric":0.10997732426303855},"test_exchange_specific_sbo_presence":{"duration":0.006293459999994866,"result":"failed","title":"Exchange Reaction SBO:0000627 Presence","summary":"    SBO:0000627 represents the term 'exchange reaction'. The Systems Biology\n    Ontology defines an exchange reaction as follows: 'A modeling process to\n    provide matter influx or efflux to a model, for example to replenish a\n    metabolic network with raw materials (eg carbon / energy sources). Such\n    reactions are conceptual, created solely for modeling purposes, and do not\n    have a  physical correspondence. Exchange reactions, often represented as\n    'R_EX_', can operate in the negative (uptake) direction or positive\n    (secretion) direction. By convention, a negative flux through an exchange\n    reaction represents uptake of the corresponding metabolite, and a positive\n    flux represent discharge.' Every exchange reaction should be annotated with\n    this. Exchange reactions differ from demand reactions in that the\n    metabolites are removed from or added to the extracellular\n    environment only.\n\n    Implementation:\n    Check if each exchange reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 exchange reactions (0.00% of all exchange\nreactions) lack annotation with the SBO term \"SBO:0000627\" for\n'exchange reaction':","data":[],"format_type":"count","metric":0.0},"test_demand_specific_sbo_presence":{"duration":0.006001333000028808,"result":"failed","title":"Demand Reaction SBO:0000628 Presence","summary":"    SBO:0000628 represents the term 'demand reaction'. The Systems Biology\n    Ontology defines a demand reaction as follows: 'A modeling process\n    analogous to exchange reaction, but which operates upon \"internal\"\n    metabolites. Metabolites that are consumed by these reactions are assumed\n    to be used in intra-cellular processes that are not part of the model.\n    Demand reactions, often represented 'R_DM_', can also deliver metabolites\n    (from intra-cellular processes that are not considered in the model).'\n    Every demand reaction should be annotated with\n    this. Demand reactions differ from exchange reactions in that the\n    metabolites are not removed from the extracellular environment, but from\n    any of the organism's compartments. Demand reactions differ from sink\n    reactions in that they are designated as irreversible.\n\n    Implementation:\n    Check if each demand reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 genes (0.00% of all demand reactions) lack\nannotation with the SBO term \"SBO:0000628\" for             'demand\nreaction':","data":[],"format_type":"count","metric":0.0},"test_sink_specific_sbo_presence":{"duration":0.005796708999980638,"result":"failed","title":"Sink Reactions SBO:0000632 Presence","summary":"    SBO:0000632 represents the term 'sink reaction'. The Systems Biology\n    Ontology defines a sink reaction as follows: 'A modeling process to\n    provide matter influx or efflux to a model, for example to replenish a\n    metabolic network with raw materials (eg carbon / energy sources). Such\n    reactions are conceptual, created solely for modeling purposes, and do not\n    have a physical correspondence. Unlike the analogous demand (SBO:....)\n    reactions, which are usually designated as irreversible, sink reactions\n    always represent a reversible uptake/secretion processes, and act as a\n    metabolite source with no cost to the cell. Sink reactions, also referred\n    to as R_SINK_, are generally used for compounds that are metabolized by\n    the cell but are produced by non-metabolic, un-modeled cellular processes.'\n    Every sink reaction should be annotated with\n    this. Sink reactions differ from exchange reactions in that the metabolites\n    are not removed from the extracellular environment, but from any of the\n    organism's compartments.\n\n    Implementation:\n    Check if each sink reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 genes (0.00% of all sink reactions) lack\nannotation with the SBO term \"SBO:0000632\" for         'sink\nreaction':","data":[],"format_type":"count","metric":0.0},"test_biomass_specific_sbo_presence":{"duration":0.00028648699998257143,"result":"passed","title":"Biomass Reactions SBO:0000629 Presence","summary":"    SBO:0000629 represents the term 'biomass production'. The Systems Biology\n    Ontology defines an exchange reaction as follows: 'Biomass production,\n    often represented 'R_BIOMASS_', is usually the optimization target reaction\n    of constraint-based models, and can consume multiple reactants to produce\n    multiple products. It is also assumed that parts of the reactants are also\n    consumed in unrepresented processes and hence products do not have to\n    reflect all the atom composition of the reactants. Formulation of a\n    biomass production process entails definition of the macromolecular\n    content (eg. cellular protein fraction), metabolic constitution of\n    each fraction (eg. amino acids), and subsequently the atomic composition\n    (eg. nitrogen atoms). More complex biomass functions can additionally\n    incorporate details of essential vitamins and cofactors required for\n    growth.'\n    Every reaction representing the biomass production should be annotated with\n    this.\n\n    Implementation:\n    Check if each biomass reaction has a non-zero \"annotation\"\n    attribute that contains the key \"sbo\" with the associated\n    value being one of the SBO terms above.","message":"A total of 0 biomass reactions (0.00% of all biomass reactions)\nlack annotation with the SBO term \"SBO:0000629\" for         'biomass\nproduction':","data":[],"format_type":"count","metric":0.0}},"score":{"sections":[{"section":"consistency","score":0.5407620092558443},{"section":"annotation_met","score":0.7531998804511668},{"section":"annotation_rxn","score":0.783415435139573},{"section":"annotation_gene","score":0.33000755857898717},{"section":"annotation_sbo","score":0.9382172776505766}],"total_score":0.7246901155700989},"cards":{"scored":{"title":"Core Tests","sections":{"consistency":{"title":"Consistency","weight":3.0,"cases":["test_stoichiometric_consistency","test_reaction_mass_balance","test_reaction_charge_balance","test_find_disconnected","test_find_reactions_unbounded_flux_default_condition"]},"annotation_met":{"title":"Annotation - Metabolites","weight":1.0,"cases":["test_metabolite_annotation_presence","test_metabolite_annotation_overview","test_metabolite_annotation_wrong_ids","test_metabolite_id_namespace_consistency"]},"annotation_rxn":{"title":"Annotation - Reactions","weight":1.0,"cases":["test_reaction_annotation_presence","test_reaction_annotation_overview","test_reaction_annotation_wrong_ids","test_reaction_id_namespace_consistency"]},"annotation_gene":{"title":"Annotation - Genes","weight":1.0,"cases":["test_gene_product_annotation_presence","test_gene_product_annotation_overview","test_gene_product_annotation_wrong_ids"]},"annotation_sbo":{"title":"Annotation - SBO Terms","weight":2.0,"cases":["test_metabolite_sbo_presence","test_metabolite_specific_sbo_presence","test_reaction_sbo_presence","test_metabolic_reaction_specific_sbo_presence","test_transport_reaction_specific_sbo_presence","test_exchange_specific_sbo_presence","test_demand_specific_sbo_presence","test_sink_specific_sbo_presence","test_gene_sbo_presence","test_gene_specific_sbo_presence","test_biomass_specific_sbo_presence"]}}},"sbml_format":{"title":"SBML","cases":["test_sbml_level","test_fbc_presence"]},"basic_info":{"title":"Basic Information","cases":["test_model_id_presence","test_metabolites_presence","test_reactions_presence","test_genes_presence","test_compartments_presence","test_metabolic_coverage","test_unconserved_metabolites","test_inconsistent_min_stoichiometry"]},"basic_met":{"title":"Metabolite Information","cases":["test_find_unique_metabolites","test_find_duplicate_metabolites_in_compartments","test_metabolites_charge_presence","test_metabolites_formula_presence","test_find_medium_metabolites"]},"basic_rxn":{"title":"Reaction Information","cases":["test_find_pure_metabolic_reactions","test_find_constrained_pure_metabolic_reactions","test_find_transport_reactions","test_find_constrained_transport_reactions","test_find_candidate_irreversible_reactions","test_find_reactions_with_partially_identical_annotations","test_find_duplicate_reactions","test_find_reactions_with_identical_genes"]},"gpr_calculations":{"title":"Gene-Protein-Reaction (GPR) Associations","cases":["test_gene_protein_reaction_rule_presence","test_transport_reaction_gpr_presence","test_protein_complex_presence"]},"test_biomass":{"title":"Biomass","cases":["test_biomass_presence","test_biomass_consistency","test_biomass_default_production","test_fast_growth_default","test_biomass_open_production","test_biomass_precursors_default_production","test_biomass_precursors_open_production","test_direct_metabolites_in_biomass","test_essential_precursors_not_in_biomass"]},"energy_metabolism":{"title":"Energy Metabolism","cases":["test_ngam_presence","test_gam_in_biomass","test_find_reversible_oxygen_reactions","test_detect_energy_generating_cycles"]},"gap_finding":{"title":"Network Topology","cases":["test_blocked_reactions","test_find_orphans","test_find_deadends","test_find_stoichiometrically_balanced_cycles","test_find_metabolites_not_produced_with_open_bounds","test_find_metabolites_not_consumed_with_open_bounds"]},"matrix":{"title":"Matrix Conditioning","cases":["test_absolute_extreme_coefficient_ratio","test_number_independent_conservation_relations","test_matrix_rank","test_degrees_of_freedom"]},"experimental":{"title":"Experimental Data Comparison","cases":["test_growth_from_data_qualitative","test_gene_essentiality_from_data_qualitative"]},"misc":{"title":"Misc. Tests","cases":["test_excreted"]}},"weights":{"test_reaction_mass_balance":1.0,"test_find_disconnected":1.0,"test_stoichiometric_consistency":3.0,"test_reaction_charge_balance":1.0,"test_metabolite_annotation_presence":1.0,"test_reaction_annotation_presence":1.0,"test_metabolite_annotation_overview":1.0,"test_reaction_annotation_overview":1.0,"test_metabolite_annotation_wrong_ids":1.0,"test_reaction_annotation_wrong_ids":1.0,"test_metabolite_id_namespace_consistency":1.0,"test_reaction_id_namespace_consistency":1.0}};
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