Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
-
Updated
Mar 20, 2024 - Python
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
List of papers about Proteins Design using Deep Learning
Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design
Protein Graph Library
The Rosetta Bio-macromolecule modeling package.
Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm
Implementation of Chroma, generative models of protein using DDPM and GNNs, in Pytorch
Fitness landscape exploration sandbox for biological sequence design.
Code to reproduce experiments in "Accelerating Bayesian Optimization for Protein Design with Denoising Autoencoders" (Stanton et al 2022)
De Novo Protein Design by Equivariantly Diffusing Oriented Residue Clouds
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
Protein Sequence Design with Deep Learning and Tooling like Monte Carlo Sampling and Analysis
SLIP is a sandbox environment for engineering protein sequences with synthetic fitness functions.
Rotamer Interaction Field Python Libraries for Computational Protein Design
Python Toolbox For Rosetta Silent Files Processing
Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure
Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design
Rosetta FunFolDes – a general framework for the computational design of functional proteins.
Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm
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.
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."