A support vector machine approach to the identification of phosphorylation sites

We describe a bioinformatics tool that can be used to predict the position of phosphorylation sites in proteins based only on sequence information. The method uses the support vector machine (SVM) statistical learning theory. The statistical models for phosphorylation by various types of kinases are...

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Bibliographic Details

Published in:	Cellular & molecular biology letters Vol. 10; no. 1; p. 73
Main Authors:	Plewczyński, Dariusz, Tkacz, Adrian, Godzik, Adam, Rychlewski, Leszek
Format:	Journal Article
Language:	English
Published:	England 2005
Subjects:	Algorithms Computational Biology Cyclic AMP-Dependent Protein Kinases - metabolism Databases, Protein Phosphorylation Protein Kinase C - metabolism Proteins - chemistry Proteins - metabolism
Online Access:	Get more information
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