RDKit is a cheminformatics library that is widely used in the field of computational chemistry. It provides a wide range of tools for working with chemical data such as molecular representation, data mining, and machine learning. The library is open-source, allowing researchers and developers to freely access and use its features.
bokehmol provides custom extensions that help plotting molecules with the Bokeh library.
It currently provides hover tools that can depict molecules on-the-fly using SMILES: no need to pre-generate the depictions and store them in memory anymore! Everything is rendered client-side in the browser so you don't even need to install rdkit in your Python environment.
Global Chem is a public dictionary of common chemical lists using the Common Chemical Name as input and SMILES/SMARTS as output organized by their respective community in a knowledge graph.github
This repository hosts an open-source benchmark for Practical Molecular Optimization (PMO), to facilitate the transparent and reproducible evaluation of algorithmic advances in molecular optimization. This repository supports 25 molecular design algorithms on 23 tasks with a particular focus on sample efficiency (oracle calls).
M2Hub aims to build the machine learning foundations for materials discovery which has a standard workflow from virtual screening/inverse design to simulation to experiment. M2Hub provides data downloading, data processing, (baseline and state-of-the-art) machine learning method implementation, evaluation pipeline and benchmark results.
ChemBERTa: A collection of BERT-like models applied to chemical SMILES data for drug design, chemical modelling, and property prediction.
GuacaMol is an open source Python package for benchmarking of models for de novo molecular design.