Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
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Updated
Jun 13, 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
An implementation of the DeepMind's AlphaFold based on PyTorch for research
Recurrent Geometric Networks for end-to-end differentiable learning of protein structure
Implementation of Alphafold 3 in Pytorch
[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding
Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.
Fast and accurate protein structure prediction
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.
Distance-based protein model quality estimation using deep ResNets
This project aims to solve a simplified version of the Protein Structure Prediction problem, represented as a combinatorial optimization task, using Reinforcement Learning.
ResNetQA: Improved protein model quality assessment by integrating sequential and pairwise features using deep learning
Source code and dataset for 2022 Publication "Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction"
OPUS-Rota5: A Highly Accurate Protein Side-chain Modeling Method with 3D-Unet and RotaFormer
An unofficial re-implementation of RoseTTAFold, a three-track deep learning model for protein structure prediction.
A machine learning model that builds amino acids into a protein model.
Source code for the manuscript: FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution
Unofficial re-implementation of IgFold, a fast antibody structure prediction method, in PyTorch.
CB513 datasets for Protein Secondary Structure Prediction
Protein Structure prediction using Hybrid Differential Evolution (HybridDE)
Alpha-Protein: Protein Contact-map Prediction Boosted by Attention
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