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Multitask learning: protein secondary structure prediction, b-values prediction and solvent-accessibility prediction
A console application for the estimation of the primary and secondary structure's elements. Input should be the FASTA-formatted "ss.txt" file generated by PDB database.
Protein secondary structure predictor
PSSpred (Protein Secondary Structure prediction) is a simple neural network training algorithm for accurate protein secondary structure prediction. It first collects multiple sequence alignments using PSI-BLAST. Amino-acid frequence and log-odds data with Henikoff weights are then used to train secondary structure, separately, based on the Rumelhart error backpropagation method. The final secondary structure prediction result is a combination of 7 neural network predictors from different profile data and parameters. The program is freely downloadable at the bottom of this page.
MUFold-ss protein secondary structure prediction implementation in pytorch
Protein Secondary Structure Prediction (PSSP) using machine learning algorithms.