List of papers about Proteins Design using Deep Learning

Protein Graph Library

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design

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

Official repository for the ProteinGym benchmarks

Versatile computational pipeline for processing protein structure data for deep learning applications.

The Rosetta Bio-macromolecule modeling package.

De Novo Protein Design by Equivariantly Diffusing Oriented Residue Clouds

Fitness landscape exploration sandbox for biological sequence design.

Implementation of Chroma, generative models of protein using DDPM and GNNs, in Pytorch

Open source biolab

Official code repository for the paper "ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers"

SaprotHub: Making Protein Modeling Accessible to All Biologists

MaSIF-neosurf: surface-based protein design for ternary complexes.

RITA is a family of autoregressive protein models, developed by LightOn in collaboration with the OATML group at Oxford and the Debora Marks Lab at Harvard.

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design

The first large protein language model trained follows structure instructions.