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Deep learning library for Chemistry based on Tensorflow

OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend.

Library with several compositional and structural material descriptors, along with a few pre-trained neural network models of material properties.

Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation.

Ensemble of automated machine learning protocols that can be run sequentially through a single command line. The program works for regression and classification problems.

Library for fast calculations of **mo**lecula**r** **fe**at**u**re**s** from 3D structures for machine learning with a focus on steric descriptors.

Aims to provide useful high-level interfaces that make ML for materials science as easy as possible.

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals.

a robust molecular representation learning framework against distribution shifts.

Library of descriptors to aid in the data-mining of materials properties, created by the Lawrence Berkeley National Laboratory.

Provides functionality for producing geometric representations of protein and RNA structures, and biological interaction networks.

Descriptor library containing a variety of fingerprinting techniques, including the Smooth Overlap of Atomic Positions (SOAP).

A Deep Learning Library for Compound and Protein Modeling DTI, Drug Property, PPI, DDI, Protein Function Prediction.

A deep learning framework (based on Chainer) with applications in Biology and Chemistry.

Enables machine learning on three-dimensional molecular structure.

High-performance ML research

A python package for optimizing chemical reactions using machine learning (contains 10 algorithms + several benchmarks).

A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models in R.

A Library for Deep Learning in Biology and Chemistry.

DGL-LifeSci is a [DGL](https://www.dgl.ai/)-based package for various applications in life science with graph neural network.

Molecular property prediction with unified API for diverse models and respresentations,

ChemML is a machine learning and informatics program suite for the analysis, mining, and modeling of chemical and materials data. (based on Tensorflow)

Directed message passing neural networks for property prediction of molecules and reactions with uncertainty and interpretation.