Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
The official sources for the RDKit library
Open Babel is a chemical toolbox designed to speak the many languages of chemical data.
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Python package for graph neural networks in chemistry and biology
The Chemistry Development Kit
Molecular Processing Made Easy.
Universal cheminformatics toolkit, utilities and database search tools
Deep Reinforcement Learning for de-novo Drug Design
Open Parser for Systematic IUPAC Nomenclature. Chemical name to structure conversion
Graph-based molecule modeling toolkit for cheminformatics
Molecule Validation and Standardization
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
Auto-QChem is an automated workflow for the generation and storage of DFT calculations for organic molecules.
A cheminformatics extension for the SQLAlchemy database toolkit.
Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.
chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.