bowman-lab/diffnets

Self-supervised neural nets to understand protein mutations

diffnets

Supervised and self-supervised autoencoders to identify the mechanistic basis for biochemical differences between protein variants.

Reference

If you use 'DiffNets' for published research, please cite us:

M.D. Ward, M.I. Zimmerman, S. Swamidass, G.R. Bowman. DiffNets: Self-supervised deep learning to identify the mechanistic basis for biochemical differences between protein variants. bioRxiv. DOI: 10.1101/2020.07.01.182725, 2020.

Dependencies

-python 3.6

-scipy, sklearn

-enspara -> which requires (MDTraj=1.8,numpy=1.14,cython, mpi4py)

-pytorch

Recommended Installation

Follow line-by-line instructions here.

While the above install should be simple to follow, a more concise install is in the works.

Building the docs / Running the tests

DiffNets uses sphinx for documentation. They are a work in progress, but can be found here.

Running the tests

Testing is in early stages. We use pytest.

cd tests
pytest

Brief tutorial

For a brief tutorial on how to use DiffNets as a command line interface (cli) please visit our documnetation page here. We recommend using the CLI to get started with diffnets.

For examples on how to use the API, view docs/example_api_scripts

Copyright

Copyright (c) 2020, Michael D. Ward, Bowman Lab

Acknowledgements

Project based on the Computational Molecular Science Python Cookiecutter version 1.3.