Please use this identifier to cite or link to this item: https://doi.org/10.1101/gr.072769.107
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dc.titleCross-species de novo identification of cis-regulatory modules with GibbsModule: Application to gene regulation in embryonic stem cells
dc.contributor.authorXie, D.
dc.contributor.authorCai, J.
dc.contributor.authorChia, N.-Y.
dc.contributor.authorNg, H.H.
dc.contributor.authorZhong, S.
dc.date.accessioned2014-10-27T08:24:53Z
dc.date.available2014-10-27T08:24:53Z
dc.date.issued2008-08
dc.identifier.citationXie, D., Cai, J., Chia, N.-Y., Ng, H.H., Zhong, S. (2008-08). Cross-species de novo identification of cis-regulatory modules with GibbsModule: Application to gene regulation in embryonic stem cells. Genome Research 18 (8) : 1325-1335. ScholarBank@NUS Repository. https://doi.org/10.1101/gr.072769.107
dc.identifier.issn10889051
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/100354
dc.description.abstractWe introduce the GibbsModule algorithm for de novo detection of cis-regulatory motifs and modules in eukaryote genomes. GibbsModule models the coexpressed genes within one species as sharing a core cis-regulatory motif and each homologous gene group as sharing a homologous cis-regulatory module (CRM), characterized by a similar composition of motifs. Without using a predetermined alignment result, GibbsModule iteratively updates the core motif shared by coexpressed genes and traces the homologous CRMs that contain the core motif. GibbsModule achieved substantial improvements in both precision and recall as compared with peer algorithms on a number of synthetic and real data sets. Applying GibbsModule to analyze the binding regions of the Krüppel-like factor (KLF) transcription factor in embryonic stem cells (ESCs), we discovered a motif that differs from a previously published KLF motif identified by a SELEX experiment, but the new motif is consistent with mutagenesis analysis. The SOX2 motif was found to be a collaborating motif to the KLF motif in ESCs. We used quantitative chromatin immunoprecipitation (ChIP) analysis to test whether GibbsModule could distinguish functional and nonfunctional binding sites. All seven tested binding sites in GibbsModule-predicted CRMs had higher ChIP signals as compared with the other seven tested binding sites located outside of predicted CRMs. GibbsModule is available at http://biocomp.bioen.uiuc.edu/ GibbsModule. ©2008 by Cold Spring Harbor Laboratory Press.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1101/gr.072769.107
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentBIOLOGICAL SCIENCES
dc.description.doi10.1101/gr.072769.107
dc.description.sourcetitleGenome Research
dc.description.volume18
dc.description.issue8
dc.description.page1325-1335
dc.description.codenGEREF
dc.identifier.isiut000258116100013
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