An ensemble method approach to investigate kinase-specific phosphorylation sites

Sutapa Datta, Subhasis MukhopadhyayDepartment of Biophysics, Molecular Biology and Bioinformatics and Distributed Information Centre for Bioinformatics, University of Calcutta, West Bengal, IndiaAbstract: Protein phosphorylation is one of the most significant and well-studied post-translational mod...

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Autores principales:	Datta S, Mukhopadhyay S
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2014
Materias:	Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/a4669c7b0e7a46cda659c9982fd8f0b6
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spelling	oai:doaj.org-article:a4669c7b0e7a46cda659c9982fd8f0b62021-12-02T02:42:21ZAn ensemble method approach to investigate kinase-specific phosphorylation sites1178-2013https://doaj.org/article/a4669c7b0e7a46cda659c9982fd8f0b62014-05-01T00:00:00Zhttp://www.dovepress.com/an-ensemble-method-approach-to-investigate-kinase-specific-phosphoryla-a16761https://doaj.org/toc/1178-2013 Sutapa Datta, Subhasis MukhopadhyayDepartment of Biophysics, Molecular Biology and Bioinformatics and Distributed Information Centre for Bioinformatics, University of Calcutta, West Bengal, IndiaAbstract: Protein phosphorylation is one of the most significant and well-studied post-translational modifications, and it plays an important role in various cellular processes. It has made a considerable impact in understanding the protein functions which are involved in revealing signal transductions and various diseases. The identification of kinase-specific phosphorylation sites has an important role in elucidating the mechanism of phosphorylation; however, experimental techniques for identifying phosphorylation sites are labor intensive and expensive. An exponentially increasing number of protein sequences generated by various laboratories across the globe require computer-aided procedures for reliably and quickly identifying the phosphorylation sites, opening a new horizon for in silico analysis. In this regard, we have introduced a novel ensemble method where we have selected three classifiers (least square support vector machine, multilayer perceptron, and k-Nearest Neighbor) and three different feature encoding parameters (dipeptide composition, physicochemical properties of amino acids, and protein–protein similarity score). Each of these classifiers is trained on each of the three different parameter systems. The final results of the ensemble method are obtained by fusing the results of all the classifiers by a weighted voting algorithm. Extensive experiments reveal that our proposed method can successfully predict phosphorylation sites in a kinase-specific manner and performs significantly better when compared with other existing phosphorylation site prediction methods.Keywords: post-translational modification, cell signaling, phosphateDatta SMukhopadhyay SDove Medical PressarticleMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol 2014, Iss Issue 1, Pp 2225-2239 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920
spellingShingle	Medicine (General) R5-920 Datta S Mukhopadhyay S An ensemble method approach to investigate kinase-specific phosphorylation sites
description	Sutapa Datta, Subhasis MukhopadhyayDepartment of Biophysics, Molecular Biology and Bioinformatics and Distributed Information Centre for Bioinformatics, University of Calcutta, West Bengal, IndiaAbstract: Protein phosphorylation is one of the most significant and well-studied post-translational modifications, and it plays an important role in various cellular processes. It has made a considerable impact in understanding the protein functions which are involved in revealing signal transductions and various diseases. The identification of kinase-specific phosphorylation sites has an important role in elucidating the mechanism of phosphorylation; however, experimental techniques for identifying phosphorylation sites are labor intensive and expensive. An exponentially increasing number of protein sequences generated by various laboratories across the globe require computer-aided procedures for reliably and quickly identifying the phosphorylation sites, opening a new horizon for in silico analysis. In this regard, we have introduced a novel ensemble method where we have selected three classifiers (least square support vector machine, multilayer perceptron, and k-Nearest Neighbor) and three different feature encoding parameters (dipeptide composition, physicochemical properties of amino acids, and protein–protein similarity score). Each of these classifiers is trained on each of the three different parameter systems. The final results of the ensemble method are obtained by fusing the results of all the classifiers by a weighted voting algorithm. Extensive experiments reveal that our proposed method can successfully predict phosphorylation sites in a kinase-specific manner and performs significantly better when compared with other existing phosphorylation site prediction methods.Keywords: post-translational modification, cell signaling, phosphate
format	article
author	Datta S Mukhopadhyay S
author_facet	Datta S Mukhopadhyay S
author_sort	Datta S
title	An ensemble method approach to investigate kinase-specific phosphorylation sites
title_short	An ensemble method approach to investigate kinase-specific phosphorylation sites
title_full	An ensemble method approach to investigate kinase-specific phosphorylation sites
title_fullStr	An ensemble method approach to investigate kinase-specific phosphorylation sites
title_full_unstemmed	An ensemble method approach to investigate kinase-specific phosphorylation sites
title_sort	ensemble method approach to investigate kinase-specific phosphorylation sites
publisher	Dove Medical Press
publishDate	2014
url	https://doaj.org/article/a4669c7b0e7a46cda659c9982fd8f0b6
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An ensemble method approach to investigate kinase-specific phosphorylation sites

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