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A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules
journal contribution
posted on 2014-01-09, 00:00 authored by Wenbo Mu, Damian Roqueiro, Yang DaiTranscription factor and microRNA are two types of key regulators of gene expression. Their regulatory mechanisms are highly
complex. In this study, we propose a computational method to predict condition-specic regulatory modules that consist of
microRNAs, transcription factors, and their commonly regulated genes. We used matched global expression proles of mRNAs
and microRNAs together with the predicted targets of transcription factors and microRNAs to construct an underlying regulatory
network. Our method searches for highly scored modules from the network based on a two-step heuristic method that combines
genetic and local search algorithms. Using two matched expression datasets, we demonstrate that our method can identify highly
scored modules with statistical signicance and biological relevance. e identied regulatory modules may provide useful insights
on the mechanisms of transcription factors and microRNAs.
Funding
The research was partially supported by the Chancellor’s Discovery Fund, University of Illinois at Chicago.
History
Publisher Statement
Copyright © 2013 Wenbo Mu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Scientific World, Scientific World JournalPublisher
Hindawi Publishing CorporationLanguage
- en_US
issn
1537-744XIssue date
2013-01-01Usage metrics
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