Full metadata record
DC Field | Value | Language |
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dc.citation.number | 9 | - |
dc.citation.startPage | e53 | - |
dc.citation.title | NUCLEIC ACIDS RESEARCH | - |
dc.citation.volume | 47 | - |
dc.contributor.author | Yoon, Sora | - |
dc.contributor.author | Nguyen, HCT | - |
dc.contributor.author | Jo, Woobeen | - |
dc.contributor.author | Kim, Jinhwan | - |
dc.contributor.author | Chi, Sang-Mun | - |
dc.contributor.author | Park, Jiyoung | - |
dc.contributor.author | Kim, Seon-Young | - |
dc.contributor.author | Nam, Dougu | - |
dc.date.accessioned | 2023-12-21T19:11:07Z | - |
dc.date.available | 2023-12-21T19:11:07Z | - |
dc.date.created | 2019-03-18 | - |
dc.date.issued | 2019-05 | - |
dc.description.abstract | We present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) targets and exhibited on an average 17.0% (median 19.4%) improved gain in certainty (sensitivity + specificity). The net gain was further increased up to 32.0% (median 33.4%) by incorporating functional networks of targets. We analyzed cancer-specific biclusters and found that the PI3K/Akt signaling pathway is strongly enriched with targets of a few miRNAs in breast cancer and diffuse large B-cell lymphoma. Indeed, five independent prognostic miRNAs were identified, and repression of bicluster targets and pathway activity by miR-29 was experimentally validated. In total, 29 898 biclusters for 459 human miRNAs were collected in the BiMIR database where biclusters are searchable for miRNAs, tissues, diseases, keywords and target genes. | - |
dc.identifier.bibliographicCitation | NUCLEIC ACIDS RESEARCH, v.47, no.9, pp.e53 | - |
dc.identifier.doi | 10.1093/nar/gkz139 | - |
dc.identifier.issn | 0305-1048 | - |
dc.identifier.scopusid | 2-s2.0-85065700590 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/26411 | - |
dc.identifier.url | https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkz139/5366474 | - |
dc.identifier.wosid | 000473756300005 | - |
dc.language | 영어 | - |
dc.publisher | Oxford University Press | - |
dc.title | Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets | - |
dc.type | Article | - |
dc.description.isOpenAccess | TRUE | - |
dc.relation.journalWebOfScienceCategory | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | PATHWAY | - |
dc.subject.keywordPlus | CANCER | - |
dc.subject.keywordPlus | GENE-EXPRESSION | - |
dc.subject.keywordPlus | REGULATORY MODULES | - |
dc.subject.keywordPlus | MIRNA | - |
dc.subject.keywordPlus | PREDICTION | - |
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