Popular GitHub Repositories for Protein Fitness

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

List of papers about Proteins Design using Deep Learning

To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released

Using artificial intelligence and genetic algorithms to automatically write programs. Tutorial: http://www.primaryobjects.com/cms/article149

Implementation of the model from "ProGen: Language Modeling for Protein Generation"

Generation of protein sequences and evolutionary alignments via discrete diffusion models

Diffusion models of protein structure; trigonometry and attention are all you need!

SparkyFitness: Built for Families. Powered by AI. Track food, fitness, water, and health — together.

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Colab Notebooks covering deep learning tools for biomolecular structure prediction and design

Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm

Scientific Large Language Models: A Survey on Biological & Chemical Domains

GearNet and Geometric Pretraining Methods for Protein Structure Representation Learning, ICLR'2023 (https://arxiv.org/abs/2203.06125)

[ICLR 2024] Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold for protein folding

A collection of research papers for AI-based protein design

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

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

Official Implemetation of DPLM (ICML'24) - Diffusion Language Models Are Versatile Protein Learners