Standardized data set for machine learning of protein structure
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Updated
Nov 18, 2020 - Python
Standardized data set for machine learning of protein structure
Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019
Saprot: Protein Language Model with Structural Alphabet
De novo protein structure prediction using iteratively predicted structural constraints
A Python 3 version of the protein descriptor package propy
Python Toolbox For Rosetta Silent Files Processing
MOLeculAR structure annoTator
Deep learning based alignment-free method for protein family modeling and prediction
Graph neural network for generating novel amino acid sequences that fold into proteins with predetermined topologies.
Guided Conditional Wasserstein GAN for De Novo Protein Design
Web application for protein-ligand binding sites analysis and visualization
Computational predictions of protein attributes associated with COVID-19 using Data Science techniques
Python Toolbox For Rosetta Silent Files Processing
BioSeq2vec: learning deep representation of biological sequences using LSTM Encoder-Decoder
Computes the percent of the residues in each protein sequence that have been identified, based on a list of identified peptides. A graphical user interface (GUI) is provided to allow the user to select the input files, set the options, and browse the coverage results.
A Deep Learning based protein flexibility prediction tool.
pmUE (Protein Modelling Unreal Engine) - a repo for constructing a molecule visualizer plugin in Unreal
A machine learning model that builds amino acids into a protein model.
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