Implementation of the HP protein folding model with commands line interface
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Updated
Nov 24, 2023 - Python
Implementation of the HP protein folding model with commands line interface
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
Algoritmo para o cálculo de RMSD para proteínas otimizadas com o modelo 3D AB Off-Lattice.
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.
Multi-S3P: Protein Secondary Structure Prediction with Specialized Multi-Network and Self-Attention-based Deep Learning Model
An unofficial re-implementation of DeepAb, an interpretable deep learning model for antibody structure prediction.
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
Unofficial re-implementation of IgFold, a fast antibody structure prediction method, in PyTorch.
Protein Secondary Structure Prediction project with RNNs and Transformers
Hybridized distance- and contact-based hierarchical protein folding
ResNetQA: Improved protein model quality assessment by integrating sequential and pairwise features using deep learning
Code for paper "Adversarial Attacks on Protein Language Models", Ginevra Carbone, Francesca Cuturello, Luca Bortolussi, Alberto Cazzaniga (2022).
A transformer network trained to predict end-to-end single sequence protein structure as a set of angles given amino acid sequences.
personal RE-implementation of GANcon paper
A machine learning model that builds amino acids into a protein model.
OPUS-Rota5: A Highly Accurate Protein Side-chain Modeling Method with 3D-Unet and RotaFormer
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