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Starred repositories
Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning
Simple protein-ligand complex simulation with OpenMM
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
MaSIF-neosurf: surface-based protein design for ternary complexes.
CReM: chemically reasonable mutations framework
cuEquivariance is a math library that is a collective of low-level primitives and tensor ops to accelerate widely-used models, like DiffDock, MACE, Allegro and NEQUIP, based on equivariant neural n…
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
⚡ TabPFN: Foundation Model for Tabular Data ⚡
OpenMM-based framework for absolute and relative binding free energy calculations with the Alchemical Transfer Method
A decorator to aid in annotating logs for easier reading and searching
MolWall: "Wall of molecules" interface to see and rate molecules
All-atom protein generation using latent diffusion, with compositional function and taxonomic prompts. http://bit.ly/plaid-proteins
ShellSage saves sysadmins’ sanity by solving shell script snafus super swiftly
MoleculeBind is a machine-learning framework for chemistry, where we target unifying various molecular representations into one common latent space (SELFIES, SMILES, Graph, Structures, Fingerprints…
Official repository for the Boltz-1 biomolecular interaction model
Recursion's molecular foundation model
Machine Learning in Drug Discovery Resources 2024
Computations and statistics on manifolds with geometric structures.
Practical Cheminformatics Tutorials
Compilation of literature examples of generative drug design that demonstrate experimental validation
Merging, linking and placing compounds by stitching bound compounds together like a reanimated corpse
Message Passing Neural Networks for Molecule Property Prediction
The bedside arrival of blockbuster medicines like ibrutinib and osimertinib changed the narrative on oncogene-driven cancers. How? Cysteine. Reporting in 2024, Takahashi et al. comprehensively map …