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 <yuanqing.wang@choderalab.org><wangyq@wangyq.net> (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.