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dc.contributor.authorHuang, HDen_US
dc.contributor.authorLee, TYen_US
dc.contributor.authorTzeng, SWen_US
dc.contributor.authorHorng, JTen_US
dc.date.accessioned2014-12-08T15:18:49Z-
dc.date.available2014-12-08T15:18:49Z-
dc.date.issued2005-07-01en_US
dc.identifier.issn0305-1048en_US
dc.identifier.urihttp://dx.doi.org/10.1093/nar/gki471en_US
dc.identifier.urihttp://hdl.handle.net/11536/13528-
dc.description.abstractKinasePhos is a novel web server for computationally identifying catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the profile hidden Markov model, computational models are learned from the kinase-specific groups of the phosphorylation sites. After evaluating the learned models, the model with highest accuracy was selected from each kinase-specific group, for use in a web-based prediction tool for identifying protein phosphorylation sites. Therefore, this work developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. The prediction tool is freely available at http://KinasePhos.mbc. nctu.edu.tw/.en_US
dc.language.isoen_USen_US
dc.titleKinasePhos: a web tool for identifying protein kinase-specific phosphorylation sitesen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/nar/gki471en_US
dc.identifier.journalNUCLEIC ACIDS RESEARCHen_US
dc.citation.volume33en_US
dc.citation.issueen_US
dc.citation.spageW226en_US
dc.citation.epageW229en_US
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000230271400042-
dc.citation.woscount121-
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