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GRIP-Tomo: GRaph Identification of Proteins in Tomograms

Tests Documentation Status

A pipeline to help identify and classify structures in tomography data using global and local topological (network) features.

The package consists of 3 core modules:

  1. pdb2graph.py - converts a PDB structure into a graph network.
  2. density2graph.py - converts a 3D density to a graph.
  3. graph2class.py - measures graph features and classifies

Documentation


Quickstart guide:

  1. open terminal / command prompt
  2. clone the repository: git clone https://github.com/EMSL-Computing/grip-tomo
  3. install the dependencies: pip install -r /path/to/requirements.txt
  4. run tests: cd path/to/grip_tomo/ then python _test_basic.py
  5. review example notebook, grip_tomo/example_notebook.ipynb
    • To interact with .ipynb files install Jupyter-lab

Citation

Please cite this work if you use it:

George, A, Kim, DN, Moser, T, Gildea, IT, Evans, JE, Cheung, MS. Graph identification of proteins in tomograms (GRIP-Tomo). Protein Science. 2023; 32( 1):e4538. https://doi.org/10.1002/pro.4538


See the included license and disclaimer files

August George, PNNL, 2022

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A graph-based method to identify proteins in tomograms

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  • Python 68.2%
  • Jupyter Notebook 31.8%