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25 search results found

Graphein ⭐ 932

Protein Graph Library

Paddlehelix ⭐ 729

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

Lightdock ⭐ 234

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

Proteinflow ⭐ 151

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

De Novo Protein Design by Equivariantly Diffusing Oriented Residue Clouds

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.

Chroma Pytorch ⭐ 63

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

Tr Rosetta Pytorch ⭐ 54

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

Timed Design ⭐ 34

Protein Sequence Design with Deep Learning and Tooling like Monte Carlo Sampling and Analysis

Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure

Deepcriticallearning ⭐ 26

Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.

Proteinnpt ⭐ 24

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

Cc_protein_origami ⭐ 18

Design platform for creating single-chain polyhedral cages made from coiled-coil building modules

Walk Jump ⭐ 18

Official repository for discrete Walk-Jump Sampling (dWJS)

PDBench is a dataset and software package for evaluating fixed-backbone sequence design algorithms.

SLIP is a sandbox environment for engineering protein sequences with synthetic fitness functions.

A bare metal Python library for building and manipulating protein molecular structures

Trdesign Motif ⭐ 8

Codebase for our preprint using trRosetta to design proteins with discontinuous functional sites, found here: https://www.biorxiv.org/content/10.1101/2020.11.29

An ML-feature processing library for biological sequences.

Deep learning for protein science

Directed_evolution ⭐ 7

Protein Design by Machine Learning guided Directed Evolution

Bayesian optimization with prescreening of search space via supervised outlier detection

Rosettasilenttoolbox ⭐ 6

Python Toolbox For Rosetta Silent Files Processing

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

Rotamer Interaction Field Python Libraries for Computational Protein Design

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