protein-structure-prediction

Implementation of Alphafold 3 from Google Deepmind in Pytorch

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

An implementation of the DeepMind's AlphaFold based on PyTorch for research

Recurrent Geometric Networks for end-to-end differentiable learning of protein structure

Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.

[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding

Nature Biotechnology: Ultra-fast, sensitive detection of protein remote homologs using deep dense retrieval

Structural Bioinformatics is awesome. Throw your textbook in the garbage, light the garbage can on fire, and blend the ashes into your cold brew almond milk latte and read this.

De novo protein structure prediction using iteratively predicted structural constraints

Fast and accurate protein structure prediction

Fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes

A Rust implementation of the LightDock macromolecular docking software

A toolkit developed to predict and analyze PROTAC-mediated ternary complexes using AlphaFold3 and Boltz-1.

An interactive visual simulator for distance-based protein folding

PyMissense creates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.

Differentiable Pairing using Alignment-based Language Models

NetSurfP 3.0: Protein secondary structure and relative solvent accessibility prediction

Python rich client for visual protein Sequence to Structure Analysis