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
An implementation of the DeepMind's AlphaFold based on PyTorch for research
Recurrent Geometric Networks for end-to-end differentiable learning of protein structure
Colab Notebooks covering deep learning tools for biomolecular structure prediction and design
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
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
Prospr is a universal toolbox for protein structure prediction within the HP-model. The Python package is based on a C++ core, which gives Prospr its high performance. The C++ core is made available as a separate zip file to facilitate high-performance computing applications. The package comes with many prediction algorithms and datasets to use.
NetSurfP 3.0: Protein secondary structure and relative solvent accessibility prediction
Python rich client for visual protein Sequence to Structure Analysis
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