Conference Paper: ProteoMirExpress: inferring microRNA-centered regulatory networks from high-throughput proteomic and transcriptome data

TitleProteoMirExpress: inferring microRNA-centered regulatory networks from high-throughput proteomic and transcriptome data
Authors
KeywordsMicroRNA
Microarray
Proteomics
Regulatory network
Bioinformatics
Issue Date2013
Citation
The 2013 Joint Conference of the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 12th European Conference on Computational Biology (ECCB), Berlin, Germany, 19-23 July 2013. How to Cite?
AbstractMicroRNAs (miRNAs) regulate gene expression through translational repression and RNA degradation. Recently developed high-throughput proteomic methods measure gene expression changes at protein levels, and therefore can reveal the direct effects of miRNAs’ translational repression. Here, we present a web server, ProteoMirExpress that integrates proteomic and mRNA expression data together to infer miRNA-centered regulatory networks. With both high throughput data from the users, ProteoMirExpress is able to discover not only miRNA targets that have mRNA decreased, but also subgroups of targets whose proteins are suppressed but mRNAs are not significantly changed or whose mRNAs are decreased but proteins are not significantly changed, which were usually ignored by most current methods. Furthermore, both direct and indirect targets of miRNAs can be detected. Therefore ProteoMirExpress provides more comprehensive miRNA-centered regulatory networks. We use several published data to assess the quality of our inferred networks and prove the value of our server. ProteoMirExpress is available at http://jjwanglab.org/ProteoMirExpress, with free access to academic users.
Persistent Identifierhttp://hdl.handle.net/10722/189747

 

DC FieldValueLanguage
dc.contributor.authorQin, Jen_US
dc.contributor.authorLi, MJen_US
dc.contributor.authorWang, Pen_US
dc.contributor.authorWong, NSen_US
dc.contributor.authorWong, MPen_US
dc.contributor.authorXia, Z-
dc.contributor.authorTsao, GSW-
dc.contributor.authorZhang, MQ-
dc.contributor.authorWang, JJ-
dc.date.accessioned2013-09-17T14:56:02Z-
dc.date.available2013-09-17T14:56:02Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 Joint Conference of the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 12th European Conference on Computational Biology (ECCB), Berlin, Germany, 19-23 July 2013.en_US
dc.identifier.urihttp://hdl.handle.net/10722/189747-
dc.description.abstractMicroRNAs (miRNAs) regulate gene expression through translational repression and RNA degradation. Recently developed high-throughput proteomic methods measure gene expression changes at protein levels, and therefore can reveal the direct effects of miRNAs’ translational repression. Here, we present a web server, ProteoMirExpress that integrates proteomic and mRNA expression data together to infer miRNA-centered regulatory networks. With both high throughput data from the users, ProteoMirExpress is able to discover not only miRNA targets that have mRNA decreased, but also subgroups of targets whose proteins are suppressed but mRNAs are not significantly changed or whose mRNAs are decreased but proteins are not significantly changed, which were usually ignored by most current methods. Furthermore, both direct and indirect targets of miRNAs can be detected. Therefore ProteoMirExpress provides more comprehensive miRNA-centered regulatory networks. We use several published data to assess the quality of our inferred networks and prove the value of our server. ProteoMirExpress is available at http://jjwanglab.org/ProteoMirExpress, with free access to academic users.-
dc.languageengen_US
dc.relation.ispartofISMB/ECCB 2013 Joint Conferenceen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectMicroRNA-
dc.subjectMicroarray-
dc.subjectProteomics-
dc.subjectRegulatory network-
dc.subjectBioinformatics-
dc.titleProteoMirExpress: inferring microRNA-centered regulatory networks from high-throughput proteomic and transcriptome dataen_US
dc.typeConference_Paperen_US
dc.identifier.emailWong, NS: nswong@hku.hken_US
dc.identifier.emailWong, MP: mwpik@hku.hk-
dc.identifier.emailXia, Z: zyxia@hku.hk-
dc.identifier.emailTsao, GSW: gswtsao@hku.hk-
dc.identifier.emailZhang, MQ: mqzhang@hku.hk-
dc.identifier.emailWang, JJ: junwen@hku.hk-
dc.identifier.authorityWong, NS=rp00340en_US
dc.description.naturepostprint-
dc.identifier.hkuros221780en_US
dc.identifier.hkuros224190-

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