Lysine acetylation sites prediction using an ensemble of support vector machine classifiers

DOI10.1016/j.jtbi.2010.01.013zbMath1406.92223OpenAlexW2084246818WikidataQ43189801 ScholiaQ43189801MaRDI QIDQ1715455

Erdal Karapınar

Publication date: 4 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.2010.01.013

zbMATH Keywords

bioinformaticsSVMensembleacetylated proteinsEnsemblePailPWMs

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Biochemistry, molecular biology (92C40)

Related Items (6)

A method to distinguish between lysine acetylation and lysine methylation from protein sequences ⋮ CE-PLoc: An ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition ⋮ Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC ⋮ Dforml(KNN)-PseAAC: detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components ⋮ BacPP: bacterial promoter prediction -- a tool for accurate sigma-factor specific assignment in enterobacteria ⋮ EnsemblePail

Uses Software

• pkaPS

Cites Work

• Unnamed Item
• Unnamed Item

This page was built for publication: Lysine acetylation sites prediction using an ensemble of support vector machine classifiers