DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Hyung-Seok | ko |
dc.contributor.author | Kim, Youngchul | ko |
dc.contributor.author | Cho, Kwang-Hyun | ko |
dc.contributor.author | Park, Taesung | ko |
dc.date.accessioned | 2013-03-12T20:41:04Z | - |
dc.date.available | 2013-03-12T20:41:04Z | - |
dc.date.created | 2012-07-04 | - |
dc.date.created | 2012-07-04 | - |
dc.date.issued | 2013-01 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, v.7, no.1, pp.38 - 57 | - |
dc.identifier.issn | 1748-5673 | - |
dc.identifier.uri | http://hdl.handle.net/10203/103458 | - |
dc.description.abstract | Since eukaryotic transcription is regulated by sets of Transcription Factors (TFs) having various transcriptional time delays, identification of temporal combinations of activated TFs is important to reconstruct Transcriptional Regulatory Networks (TRNs). Our methods combine time course microarray data, information on physical binding between the TFs and their targets and the regulatory sequences of genes using a log-linear model to reconstruct dynamic functional TRNs of the yeast cell cycle and human apoptosis. In conclusion, our results suggest that the proposed dynamic motif search method is more effective in reconstructing TRNs than the static motif search method. | - |
dc.language | English | - |
dc.publisher | INDERSCIENCE ENTERPRISES LTD | - |
dc.subject | GENE-EXPRESSION DATA | - |
dc.subject | FACTOR-BINDING SITES | - |
dc.subject | CELL-CYCLE | - |
dc.subject | SACCHAROMYCES-CEREVISIAE | - |
dc.subject | COMPUTATIONAL GENOMICS | - |
dc.subject | BAYESIAN NETWORKS | - |
dc.subject | YEAST | - |
dc.subject | IDENTIFICATION | - |
dc.subject | MODULES | - |
dc.subject | ELEMENTS | - |
dc.title | Integrative analysis of time course microarray data and DNA sequence data via log-linear models for identifying dynamic transcriptional regulatory networks | - |
dc.type | Article | - |
dc.identifier.wosid | 000312496000003 | - |
dc.identifier.scopusid | 2-s2.0-84871435097 | - |
dc.type.rims | ART | - |
dc.citation.volume | 7 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 38 | - |
dc.citation.endingpage | 57 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS | - |
dc.identifier.doi | 10.1504/IJDMB.2013.050975 | - |
dc.contributor.localauthor | Cho, Kwang-Hyun | - |
dc.contributor.nonIdAuthor | Choi, Hyung-Seok | - |
dc.contributor.nonIdAuthor | Kim, Youngchul | - |
dc.contributor.nonIdAuthor | Park, Taesung | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | TRN | - |
dc.subject.keywordAuthor | transcriptional regulatory network | - |
dc.subject.keywordAuthor | transcription factor binding motif | - |
dc.subject.keywordAuthor | eukaryotic transcription | - |
dc.subject.keywordAuthor | log-linear model | - |
dc.subject.keywordAuthor | heterogeneous data integration | - |
dc.subject.keywordPlus | GENE-EXPRESSION DATA | - |
dc.subject.keywordPlus | FACTOR-BINDING SITES | - |
dc.subject.keywordPlus | CELL-CYCLE | - |
dc.subject.keywordPlus | SACCHAROMYCES-CEREVISIAE | - |
dc.subject.keywordPlus | COMPUTATIONAL GENOMICS | - |
dc.subject.keywordPlus | BAYESIAN NETWORKS | - |
dc.subject.keywordPlus | YEAST | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | MODULES | - |
dc.subject.keywordPlus | ELEMENTS | - |
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