https://github.com/choderalab/gimlet

Graph Inference on MoLEcular Topology
https://github.com/choderalab/gimlet

graph-theory molecular-modeling tensorflow-gpu

Last synced: 3 months ago
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Graph Inference on MoLEcular Topology

• Host: GitHub
• URL: https://github.com/choderalab/gimlet
• Owner: choderalab
• License: other
• Created: 2019-04-22T20:33:12.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-03-25T00:21:46.000Z (over 1 year ago)
• Last Synced: 2024-07-04T02:12:53.568Z (4 months ago)
• Topics: graph-theory, molecular-modeling, tensorflow-gpu
• Language: Python
• Homepage:
• Size: 27.4 MB
• Stars: 26
• Watchers: 11
• Forks: 9
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# gimlet

Graph Inference on MoLEcular Topology. A package for modelling, learning, and inference on molecular topological space written in Python and TensorFlow.

## Dependencies

`gimlet` doesn't depend on _any_ packages except `TensorFlow 2.0 `, and `pandas` and `pytest`, if you must.

## Examples

https://github.com/choderalab/gimlet/blob/master/lime/scripts/notebooks/190728_yuanqing_gn_with_gru_on_sereina_riniker_dataset.ipynb

## Authors

- yuanqing wang `` (while at Chodera Lab at Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine, and the City College of the City University of New York.)

## Manifest

* `gin/` the core (and fun) part of the package.

    * `i_o/` reading and writing popular molecule embedding/representing structures.

    * `deterministic/` property predictions, conformer and charge generations. 

    * `probabilistic/` molecular machine learning through graph networks.

* `lime/` auxiliary scripts.

    * `for_biologists/` ready-to-use modules and scripts.

    * `architectures/` off-the-shelf model architectures developed elsewhere.

    * `scripts/` fun scripts we used to generate data and hypothesis.

    * `trained_models/` _Nomen est omen_.