An unofficial re-implementation of DeepAb, an interpretable deep learning model for antibody structure prediction.
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Updated
Jul 24, 2023 - Python
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
Implementation of the HP protein folding model with commands line interface
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Python implementation of Markov state model-based adaptive sampling guided by SAXS and hybrid information.
Distance- and orientation-based Covariational threadER
Hybridized distance- and contact-based hierarchical protein folding
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
Fragment assembly ab initio protein folding
Transformer model for protein structure prediction
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
PyMissense creates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.
Algoritmo para o cálculo de RMSD para proteínas otimizadas com o modelo 3D AB Off-Lattice.
Code for paper "Adversarial Attacks on Protein Language Models", Ginevra Carbone, Francesca Cuturello, Luca Bortolussi, Alberto Cazzaniga (2022).
Repository with scripts and data generated during my internship at Institut Pasteur of Paris
Performing a regression task for estimating residue size based on given physicochemical properties of protein tertiary structures (CASP 5-9).
A transformer network trained to predict end-to-end single sequence protein structure as a set of angles given amino acid sequences.
Deep Learning for Protein Structure Prediction
CASP15 performance benchmarking of the state-of-the-art protein structure prediction methods
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