ArticleNucleic acids research2019
Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Scanning sample-specific miRNA regulation from bulk and single-cell RNA-sequencing data.BMC biology · 2024Article
- Exploring the clinical implications and applications of exosomal miRNAs in gliomas: a comprehensive study.Cancer cell international · 2024Review
- Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data.BMC bioinformatics · 2021Article
- Screening and identification of differentially expressed microRNAs in diffuse large B-cell lymphoma based on microRNA microarray.Oncology letters · 2021Article
- TSCCA: A tensor sparse CCA method for detecting microRNA-gene patterns from multiple cancers.PLoS computational biology · 2021Article
- Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma.Life science alliance · 2021Article
- Selected Research Articles from the 2019 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC).BMC genomics · 2020Article
- ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder.Frontiers in genetics · 2020Article
- Scalable biclustering - the future of big data exploration?GigaScience · 2019Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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