Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition

DOI10.1016/j.jtbi.2014.07.003zbMath1343.92387OpenAlexW1990678622WikidataQ30364744 ScholiaQ30364744MaRDI QIDQ739676

Loris Nanni, Alessandra Lumini, Sheryl Brahnam

Publication date: 19 August 2016

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2014.07.003

zbMATH Keywords

support vector machinesmachine learningensemble of classifiersprotein descriptorsprotein structure class

Mathematics Subject Classification ID

Protein sequences, DNA sequences (92D20) Computational methods for problems pertaining to biology (92-08)

Related Items (6)

A composite approach to protein tertiary structure prediction: hidden Markov model based on lattice ⋮ Precision assessment of some supervised and unsupervised algorithms for genotype discrimination in the genus \textit{pisum} using SSR molecular data ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC ⋮ SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins ⋮ Alpha influenza virus infiltration prediction using virus-human protein-protein interaction network

Uses Software

• Matlab
• PseAAC
• propy
• iAMP-2L
• iRSpot-PseDNC
• iSNO-PseAAC
• iSNO-AAPair
• AAindex
• SCPRED

Cites Work

• Prediction of structural classes for protein sequences and domains--impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy
• Some remarks on protein attribute prediction and pseudo amino acid composition
• A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition
• High performance set of PseAAC and sequence based descriptors for protein classification
• A high-accuracy protein structural class prediction algorithm using predicted secondary structural information
• Accurate prediction of protein structural classes by incorporating predicted secondary structure information into the general form of Chou's pseudo amino acid composition

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