C++ package that provides tools for correcting structural predictions of proteins (eg. from X-Ray Crystallography or AlphaFold) using X-ray small-angle scattering (SAXS) in solution
-
Updated
Jun 5, 2024 - C++
C++ package that provides tools for correcting structural predictions of proteins (eg. from X-Ray Crystallography or AlphaFold) using X-ray small-angle scattering (SAXS) in solution
A Python package to manage protein design workflows on computing clusters and local machines. Documentation can be found here: https://protflow.readthedocs.io/en/latest/
The Rosetta Bio-macromolecule modeling package.
Protein Graph Library
SaprotHub: Making Protein Modeling Accessible to All Biologists
Official repository for discrete Walk-Jump Sampling (dWJS)
Deep learning for protein science
List of papers about Proteins Design using Deep Learning
Complex-based Ligand-Binding Proteins Redesign by Equivariant Diffusion-based Generative Models
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
DE-STRESS is a model evaluation pipeline that aims to make protein design more reliable and accessible.
A library of tools for protein design
Protein Sequence Design with Deep Learning and Tooling like Monte Carlo Sampling and Analysis
Code to reproduce experiments in "Accelerating Bayesian Optimization for Protein Design with Denoising Autoencoders" (Stanton et al 2022)
Use generative ML to design new proteins using this simple, hackable implementation of protein transformer models
The first large protein language model trained follows structure instructions.
Benchmark for Biophysical Sequence Optimization Algorithms
Reveal protein energy centers.
Calculation of interatomic interactions in molecular structures
Add a description, image, and links to the protein-design topic page so that developers can more easily learn about it.
To associate your repository with the protein-design topic, visit your repo's landing page and select "manage topics."