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A descent project structure for making and sharing science work in Computational Biophysics.

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Computational Biophysics Research Project

A descent project structure for doing and sharing science work in Computational Biophysics.

Project Organization

├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── config.yaml        <- A configuration file for the scripts.
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├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
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├── docs               <- A default Sphinx project; see sphinx-doc.org for details
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├── ccenv.yml          <- A Conda environmet file.
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├── misc
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├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
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├── output
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├── pdb
│   ├── processed
│   └── raw
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├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
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├── src
│   ├── data           <- Scripts to download or generate data
│   │   ├── make_dataset.py
│   │   └── make_pdb.py
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
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├── tmp                <- for temporary files
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├── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io
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└── .env               <- Stores environment variables for Dotenv module. Do not track with version control.

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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A descent project structure for making and sharing science work in Computational Biophysics.

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