Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion
Abstract
MOTIVATION: Identification of microRNA regulatory modules (MiRMs) will aid deciphering aberrant transcriptional regulatory network in cancer but is computationally challenging. Existing methods are stochastic or require a fixed number of regulatory modules. RESULTS: We propose Mirsynergy, an efficient deterministic overlapping clustering algorithm adapted from a recently developed framework. Mirsynergy operates in two stages: it first forms MiRMs based on co-occurring microRNA (miRNA) targets and then expands each MiRM by greedily including (excluding) mRNAs into (from) the MiRM to maximize the synergy score, which is a function of miRNA-mRNA and gene-gene interactions. Using expression data for ovarian, breast and thyroid cancer from The Cancer Genome Atlas, we compared Mirsynergy with internal controls and existing methods. Mirsynergy-MiRMs exhibit significantly higher functional enrichment and more coherent miRNA-mRNA expression anti-correlation. Based on Kaplan-Meier survival analysis, we proposed several prognostically promising MiRMs and envisioned their utility in cancer research. AVAILABILITY AND IMPLEMENTATION: Mirsynergy is implemented/available as an R/Bioconductor package at www.cs.utoronto.ca/∼yueli/Mirsynergy.html.
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Low expression but functional miRNA may synergistically increase RNAi activity on a subset of target mRNAs, thereby effectively enhancing the concentration of cognate miRNAs for specific mRNAs.
“In this way, low expression but functional miRNA may synergistically increase RNAi activity on a subset of target mRNAs, thereby effectively enhancing the concentration of cognate miRNAs for specific mRNAs (101, 102).”
From Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation (2018) · cites this paper as [101]
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Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation
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- Authors
- Li, Y., Liang, C., Wong, K.-C., Luo, J., & Zhang, Z.
- Affiliations
- Hunan University (CN)
- Corresponding author
- Li, Yue
- Zhang, Zhaolei
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-06-03
- Volume
- 30
- Issue
- 18
- Pages
- 2627-2635
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2143693563
- Cited by
- 83
- References
- 34
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 1 · 2023: 6 · 2022: 6 · 2021: 5 · 2020: 8 · 2019: 11 · 2018: 12 · 2017: 7 · 2016: 13 · 2015: 9 · 2014: 1
- FWCI
- 3.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- overlapping clustering, miRNA-mRNA interactions, gene-gene interaction, transcriptional regulatory networks, cancer, ovarian cancer, breast cancer, thyroid cancer, prognostic factors, functional enrichment
- MeSH terms
- Algorithms, Binding Sites, Epistasis, Genetic, Female, Humans, Neoplasms, RNA, Messenger, Cluster Analysis, Computational Biology, MicroRNAs, Gene Regulatory Networks, Transcriptome
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