Fragment assembly ab initio protein folding
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Updated
Oct 25, 2016 - C
Fragment assembly ab initio protein folding
A balance-evolution artificial bee colony algorithm for protein structure optimization based on a three-dimensional AB off-lattice model
Python implementation of Markov state model-based adaptive sampling guided by SAXS and hybrid information.
Recurrent Geometric Networks for end-to-end differentiable learning of protein structure
Recurrent Geometric Networks for end-to-end differentiable learning of protein structure
This project aims to solve a simplified version of the Protein Structure Prediction problem, represented as a combinatorial optimization task, using Reinforcement Learning.
Source code for the manuscript: FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution
Fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes
Distance-based protein model quality estimation using deep ResNets
Implementação do algortimo Nelder-Mead em CUDA C++.
Algoritmo para o cálculo de RMSD para proteínas otimizadas com o modelo 3D AB Off-Lattice.
Peptide structure prediction by global optimization of a potential energy function
An implementation of the DeepMind's AlphaFold based on PyTorch for research
An interactive visual simulator for distance-based protein folding
Hybridized distance- and contact-based hierarchical protein folding
A machine learning model that builds amino acids into a protein model.
Protein Structure prediction using Hybrid Differential Evolution (HybridDE)
ResNetQA: Improved protein model quality assessment by integrating sequential and pairwise features using deep learning
Alpha-Protein: Protein Contact-map Prediction Boosted by Attention
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