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dc.contributor.authorLee, Tzong-Yien_US
dc.contributor.authorHsu, Justin Bo-Kaien_US
dc.contributor.authorChang, Wen-Chien_US
dc.contributor.authorHuang, Hsien-Daen_US
dc.date.accessioned2014-12-08T15:37:55Z-
dc.date.available2014-12-08T15:37:55Z-
dc.date.issued2011-01-01en_US
dc.identifier.issn0305-1048en_US
dc.identifier.urihttp://dx.doi.org/10.1093/nar/gkq970en_US
dc.identifier.urihttp://hdl.handle.net/11536/26052-
dc.description.abstractProtein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of experimental phosphorylation sites that has been identified by mass spectrometry-based proteomics, the desire to explore the networks of protein kinases and substrates is motivated. Manning et al. have identified 518 human kinase genes, which provide a starting point for comprehensive analysis of protein phosphorylation networks. In this study, a knowledgebase is developed to integrate experimentally verified protein phosphorylation data and protein-protein interaction data for constructing the protein kinase-substrate phosphorylation networks in human. A total of 21 110 experimental verified phosphorylation sites within 5092 human proteins are collected. However, only 4138 phosphorylation sites (similar to 20%) have the annotation of catalytic kinases from public domain. In order to fully investigate how protein kinases regulate the intracellular processes, a published kinase-specific phosphorylation site prediction tool, named KinasePhos is incorporated for assigning the potential kinase. The web-based system, RegPhos, can let users input a group of human proteins; consequently, the phosphorylation network associated with the protein subcellular localization can be explored. Additionally, time-coursed microarray expression data is subsequently used to represent the degree of similarity in the expression profiles of network members. A case study demonstrates that the proposed scheme not only identify the correct network of insulin signaling but also detect a novel signaling pathway that may cross-talk with insulin signaling network. This effective system is now freely available at http://RegPhos.mbc.nctu.edu.tw.en_US
dc.language.isoen_USen_US
dc.titleRegPhos: a system to explore the protein kinase-substrate phosphorylation network in humansen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/nar/gkq970en_US
dc.identifier.journalNUCLEIC ACIDS RESEARCHen_US
dc.citation.volume39en_US
dc.citation.issueen_US
dc.citation.spageD777en_US
dc.citation.epageD787en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000285831700123-
dc.citation.woscount17-
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