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.