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Article: CMGRN: a web server for constructing multilevel gene regulatory networks using ChIP-seq and gene expression data

TitleCMGRN: a web server for constructing multilevel gene regulatory networks using ChIP-seq and gene expression data
Authors
Issue Date2014
PublisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
Citation
Bioinformatics, 2014, v. 30 n. 8, p. 1190-1192 How to Cite?
AbstractSUMMARY: ChIP-seq technology provides an accurate characterization of transcription or epigenetic factors binding on genomic sequences. With integration of such ChIP-based and other high-throughput information, it would be dedicated to dissecting cross-interactions among multilevel regulators, genes and biological functions. Here, we devised an integrative web server CMGRN (constructing multilevel gene regulatory networks), to unravel hierarchical interactive networks at different regulatory levels. The newly developed method used the Bayesian network modeling to infer causal interrelationships among transcription factors or epigenetic modifications by using ChIP-seq data. Moreover, it used Bayesian hierarchical model with Gibbs sampling to incorporate binding signals of these regulators and gene expression profile together for reconstructing gene regulatory networks. The example applications indicate that CMGRN provides an effective web-based framework that is able to integrate heterogeneous high-throughput data and to reveal hierarchical 'regulome' and the associated gene expression programs.
Persistent Identifierhttp://hdl.handle.net/10722/193863
ISSN
2015 Impact Factor: 5.766
2015 SCImago Journal Rankings: 4.643
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorGuan, Den_US
dc.contributor.authorShao, Jen_US
dc.contributor.authorDeng, Yen_US
dc.contributor.authorWang, Pen_US
dc.contributor.authorZhao, Zen_US
dc.contributor.authorLiang, Yen_US
dc.contributor.authorWang, JJen_US
dc.contributor.authorYan, Ben_US
dc.date.accessioned2014-01-28T06:28:40Z-
dc.date.available2014-01-28T06:28:40Z-
dc.date.issued2014en_US
dc.identifier.citationBioinformatics, 2014, v. 30 n. 8, p. 1190-1192en_US
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/193863-
dc.description.abstractSUMMARY: ChIP-seq technology provides an accurate characterization of transcription or epigenetic factors binding on genomic sequences. With integration of such ChIP-based and other high-throughput information, it would be dedicated to dissecting cross-interactions among multilevel regulators, genes and biological functions. Here, we devised an integrative web server CMGRN (constructing multilevel gene regulatory networks), to unravel hierarchical interactive networks at different regulatory levels. The newly developed method used the Bayesian network modeling to infer causal interrelationships among transcription factors or epigenetic modifications by using ChIP-seq data. Moreover, it used Bayesian hierarchical model with Gibbs sampling to incorporate binding signals of these regulators and gene expression profile together for reconstructing gene regulatory networks. The example applications indicate that CMGRN provides an effective web-based framework that is able to integrate heterogeneous high-throughput data and to reveal hierarchical 'regulome' and the associated gene expression programs.-
dc.languageengen_US
dc.publisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/-
dc.relation.ispartofBioinformaticsen_US
dc.titleCMGRN: a web server for constructing multilevel gene regulatory networks using ChIP-seq and gene expression dataen_US
dc.typeArticleen_US
dc.identifier.emailWang, JJ: junwen@hku.hken_US
dc.identifier.authorityWang, JJ=rp00280en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bioinformatics/btt761en_US
dc.identifier.pmid24389658-
dc.identifier.scopuseid_2-s2.0-84898016349-
dc.identifier.hkuros227437en_US
dc.identifier.volume30-
dc.identifier.issue8-
dc.identifier.spage1190-
dc.identifier.epage1192-
dc.identifier.isiWOS:000335001000023-
dc.publisher.placeUnited Kingdom-

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