Stars
List the AI for Science papers accepted by top conferences
List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning
Fast protein backbone generation with SE(3) flow matching.
🧬 Advanced hybrid language model for directed protein evolution. (NeurIPS 2024)
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
TopoBench is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning
List of papers about Proteins Design using Deep Learning
llama3 implementation one matrix multiplication at a time
FrameDiPT: an SE(3) diffusion model for protein structure inpainting
Awesome Protein Representation Learning
A resource repository for 3D machine learning
Papers about Structure-based Drug Design (SBDD)
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
Geometric kernels on manifolds, meshes and graphs
E(3)-Equivariant Mesh Neural Networks (AISTATS 2024)
Clifford-Steerable Convolutional Neural Networks [ICML'24]
FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation
Learning Harmonic Molecular Representations on Riemannian Manifold, ICLR, 2023
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
Code for "Learning Harmonic Molecular Representations on Riemannian Manifold", ICLR, 2023
Compressing protein structures effectively with torsion angles
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Dongcf / bio_embeddings
Forked from sacdallago/bio_embeddingsGet protein embeddings from protein sequences
Graph Neural Networks with Keras and Tensorflow 2.
To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released
Open source code for AlphaFold 2.
ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.