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Title 

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

Authors 

S YoonH C T NguyenW JoJ KimS B ChiJ ParkSeon-Young KimD Nam

Publisher 

Oxford University Press

Issue Date 

2019

Citation 

Nucleic Acids Research

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 sequencespecific 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 prognosticmiRNAs 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://doi.org/10.1093/nar/gkz139

ISSN 

0305-1048

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-07-10


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