Inferring gene regulatory networks from temporal expression profiles under time-delay and noise

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dc.contributor.authorKim, Sko
dc.contributor.authorKim, Jko
dc.contributor.authorCho, Kwang-Hyunko
dc.date.accessioned2013-03-06T22:54:59Z-
dc.date.available2013-03-06T22:54:59Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2007-08-
dc.identifier.citationCOMPUTATIONAL BIOLOGY AND CHEMISTRY, v.31, pp.239 - 245-
dc.identifier.issn1476-9271-
dc.identifier.urihttp://hdl.handle.net/10203/88751-
dc.description.abstractOrdinary differential equations (ODE) have been widely used for modeling and analysis of dynamic gene networks in systems biology. In this paper, we propose an optimization method that can infer a gene regulatory network from time-series gene expression data. Specifically, the following four cases are considered: (1) reconstruction of a gene network from synthetic gene expression data with noise, (2) reconstruction of a Dene network from synthetic gene expression data with time-delay, (3) reconstruction of a gene network from synthetic gene expression data with noise and time-delay, and (4) reconstruction of a gene network from experimental time-series data in budding yeast cell cycle. (c) 2007 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.subjectEXPONENTIAL STABILITY-
dc.subjectNEURAL-NETWORKS-
dc.subjectPERTURBATIONS-
dc.subjectYEAST-
dc.titleInferring gene regulatory networks from temporal expression profiles under time-delay and noise-
dc.typeArticle-
dc.identifier.wosid000249192700001-
dc.identifier.scopusid2-s2.0-34447651339-
dc.type.rimsART-
dc.citation.volume31-
dc.citation.beginningpage239-
dc.citation.endingpage245-
dc.citation.publicationnameCOMPUTATIONAL BIOLOGY AND CHEMISTRY-
dc.identifier.doi10.1016/j.compbiolchem.2007.03.013-
dc.contributor.localauthorCho, Kwang-Hyun-
dc.contributor.nonIdAuthorKim, S-
dc.contributor.nonIdAuthorKim, J-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorgene networks-
dc.subject.keywordAuthorinference-
dc.subject.keywordAuthoroptimization-
dc.subject.keywordAuthorordinary differential equations-
dc.subject.keywordAuthornoise-
dc.subject.keywordAuthortime-delay-
dc.subject.keywordPlusEXPONENTIAL STABILITY-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusPERTURBATIONS-
dc.subject.keywordPlusYEAST-
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