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Park, Jiyoung
Molecular Metabolism Laboratory (MML)
Research Interests
  • Obesity, diabetes, adipose tissue, cancer, cancer-associated adipocyte, dermal adipocyte, metabolic memory

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Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets

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Title
Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets
Author
Yoon, SoraNguyen, HCTJo, WoobeenKim, JinhwanChi, Sang-MunPark, JiyoungKim, Seon-YoungNam, Dougu
Issue Date
2019-05
Publisher
Oxford University Press
Citation
NUCLEIC ACIDS RESEARCH, v.47, no.9, pp.e53
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.
URI
https://scholarworks.unist.ac.kr/handle/201301/26411
URL
https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkz139/5366474
DOI
10.1093/nar/gkz139
ISSN
0305-1048
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SLS_Journal Papers
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