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BioMed Research International
Volume 2017, Article ID 7049406, 8 pages
Review Article

Methods of MicroRNA Promoter Prediction and Transcription Factor Mediated Regulatory Network

1State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, Harbin, Heilongjiang, China
2Information and Computer Engineering College, Northeast Forestry University, Harbin, Heilongjiang, China
3School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China
4Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA

Correspondence should be addressed to Yuming Zhao; moc.liamtoh@oyoymyz

Received 3 March 2017; Accepted 7 May 2017; Published 5 June 2017

Academic Editor: Weihua Chen

Copyright © 2017 Yuming Zhao 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.


MicroRNAs (miRNAs) are short (~22 nucleotides) noncoding RNAs and disseminated throughout the genome, either in the intergenic regions or in the intronic sequences of protein-coding genes. MiRNAs have been proved to play important roles in regulating gene expression. Hence, understanding the transcriptional mechanism of miRNA genes is a very critical step to uncover the whole regulatory network. A number of miRNA promoter prediction models have been proposed in the past decade. This review summarized several most popular miRNA promoter prediction models which used genome sequence features, or other features, for example, histone markers, RNA Pol II binding sites, and nucleosome-free regions, achieved by high-throughput sequencing data. Some databases were described as resources for miRNA promoter information. We then performed comprehensive discussion on prediction and identification of transcription factor mediated microRNA regulatory networks.