Effective DNA binding protein prediction by using key features via Chou's general PseAAC

DOI10.1016/j.jtbi.2018.10.027zbMath1406.92447OpenAlexW2895810213WikidataQ57476320 ScholiaQ57476320MaRDI QIDQ1716796

Swakkhar Shatabda, Sheikh Adilina, Dewan Md Farid

Publication date: 5 February 2019

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

Full work available at URL: https://doi.org/10.1016/j.jtbi.2018.10.027

zbMATH Keywords

classification algorithmfeature selectionDNA binding proteinshandling overfittingindependent test setsequence based features

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Protein sequences, DNA sequences (92D20) Software, source code, etc. for problems pertaining to biology (92-04)

Uses Software

• Scikit
• pSuc-Lys
• iEnhancer-2L
• Pse-in-One
• iDNA-Prot
• iPPI-Esml
• PseDNA-Pro
• iSuc-PseOpt
• PseKNC
• iRSpot-PseDNC
• iSS-PseDNC
• iRNA-Methyl
• Pse-analysis
• iPTM-mLys
• iACP
• iCar-PseCp
• iHyd-PseCp
• iPhos-PseEn
• pLoc-mAnimal
• pLoc-mVirus
• pLoc-mEuk
• DPP-PseAAC
• PSLDoc
• pLoc-mGneg
• pLoc-mPlant
• iHSP-PseRAAAC
• iKcr-PseEns
• iRNA-3typeA
• pLoc_bal-mGpos
• HMMBinder

Cites Work

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• pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach
• Robust \(k\)-mer frequency estimation using gapped \(k\)-mers
• Some remarks on protein attribute prediction and pseudo amino acid composition
• pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC
• Extremely randomized trees

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