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
WebGL accelerated JavaScript molecular graphics library
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
Benchmarks for generative chemistry
A Euclidean diffusion model for structure-based drug design.
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
A Python package for molecular docking with an extensive, highly-curated dataset and a set of realistic benchmark tasks for drug discovery.
Auto-QChem is an automated workflow for the generation and storage of DFT calculations for organic molecules.
The d-SEAMS C++ core engine
chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models
Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).
Simple webapp for generating small ligand conformers
Accelerated similarity searching of small molecules (bioconductor package)