Molecules
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
code for the paper "DiGress: Discrete Denoising diffusion for graph generation"
A modular framework for neural networks with Euclidean symmetry
Contains the necessary material to reproduce the content of the paper: Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes
Computations and statistics on manifolds with geometric structures.
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
Implementation of the Paper "Learning Continuous and Data-Driven Molecular Descriptors by Translating Equivalent Chemical Representations" by Robin Winter, Floriane Montanari, Frank Noe and Djork-A…
Fraction of Common Contacts Clustering Algorithm for Protein Structures
A Python package for calculating molecular features
DScribe is a python package for creating machine learning descriptors for atomistic systems.
Toolkit for free-energy calculation setup/analysis and biomolecular structure handling
Official repository for discrete Walk-Jump Sampling (dWJS)
Making Protein folding accessible to all!
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
COATI: multi-modal contrastive pre-training for representing and traversing chemical space
Materials for 2023 workshop at CCPBioSim Training Week https://www.ccpbiosim.ac.uk/events/upcoming-events/eventdetail/104/-/training-week
Implementation of FlowSite and HarmonicFlow from the paper "Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design"
Protein-ligand structure prediction
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure
Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
Implementation of E(n)-Transformer, which incorporates attention mechanisms into Welling's E(n)-Equivariant Graph Neural Network
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
A Library for Gaussian Processes in Chemistry
Framework for the rapid modeling glycans and glycoproteins.