Implementation of the HP protein folding model with commands line interface

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Distance- and orientation-based Covariational threadER

This repository contains the source code for the DebruijnExtend tool. This tool uses known secondary structures for common protein kmers to predict the most likely secondary structure. This is done using a debruijn graph approach to incorporate local homology for predicting the most probable secondary structure along a protein. Tested on mac/linux

A package-like tool that analyzes protein sequences, categorizes a protein of interest into one of two groups, predicts secondary structure based on dihedral angles/Ramachandran plots and Chou and Fasman's statistical propensity method, and does pattern search by Naive, KMP, and Bayer-Moore

Deep Learning for Protein Structure Prediction

Algoritmo para o cálculo de RMSD para proteínas otimizadas com o modelo 3D AB Off-Lattice.

Performing a regression task for estimating residue size based on given physicochemical properties of protein tertiary structures (CASP 5-9).

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

A method designed for proteome-scale sequence-based evaluation of protein-protein interfaces as defined by structural models of protein-protein interaction complexes.

Implementação do algortimo Nelder-Mead em CUDA C++.

Predict protein folding structures using ColabFold. Gain a deeper understanding of protein folding prediction with AlphaFold2 and MMseqs2. Run the Jupyter notebook on UCloud, learn to interpret results, predict protein structures of interest. Technical requirements provided. Enhance your knowledge of protein folding and AlphaFold2's principles. Fam

Unofficial re-implementation of IgFold, a fast antibody structure prediction method, in PyTorch.

An unofficial re-implementation of DeepAb, an interpretable deep learning model for antibody structure prediction.

Multi-S3P: Protein Secondary Structure Prediction with Specialized Multi-Network and Self-Attention-based Deep Learning Model

Python implementation of Markov state model-based adaptive sampling guided by SAXS and hybrid information.

Source code for the manuscript: FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution

Transformer model for protein structure prediction

Repository with scripts and data generated during my internship at Institut Pasteur of Paris

Protein contact map quality estimation by evolutionary reconciliation