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Genome-Wide Analysis of MicroRNA-Regulated Transcripts

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Bioinformatics in MicroRNA Research

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1617))

Abstract

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by either degrading transcripts or repressing translation . Over the past decade the significance of miRNAs has been unraveled by the characterization of their involvement in crucial cellular functions and the development of disease. However, continued progress in understanding the endogenous importance of miRNAs, as well as their potential uses as therapeutic tools, has been hindered by the difficulty of positively identifying miRNA targets. To face this challenge algorithmic approaches have primarily been utilized to date, but strictly mathematical models have thus far failed to produce a generally accurate, widely accepted methodology for accurate miRNA target determination. As such, several laboratory-based, comprehensive strategies for experimentally identifying all cellular miRNA regulations simultaneously have recently been developed. This chapter discusses the advantages and limitations of both classic and comprehensive strategies for miRNA target prediction .

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Authors and Affiliations

  1. Department of Biology, East Georgia State College, Swainsboro, GA, 30401, USA

    David Chevalier & Glen M. Borchert Ph.D.

  2. Department of Pharmacology, University of South Alabama, Mobile, AL, 36688, USA

    Glen M. Borchert Ph.D.

Authors
  1. David Chevalier
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  2. Glen M. Borchert Ph.D.
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Correspondence to Glen M. Borchert Ph.D. .

Editor information

Editors and Affiliations

  1. School of Computing, University of South Alabama, Mobile, Alabama, USA

    Jingshan Huang

  2. Department of Pharmacology, University of South Alabama, Mobile, Alabama, USA

    Glen M. Borchert

  3. Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA

    Dejing Dou

  4. Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, Kansas, USA

    Jun (Luke) Huan

  5. School of Bioengineering, Qilu University of Technology, Jinan, Shandong, China

    Wenjun Lan

  6. Mitchel Cancer Institute, University of South Alabama, Mobile, Alabama, USA

    Ming Tan

  7. Department of Endocrinology, First Affiliated Hospital, Kunming Medical University, Kunming, Yunnan, China

    Bin Wu

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Chevalier, D., Borchert, G.M. (2017). Genome-Wide Analysis of MicroRNA-Regulated Transcripts. In: Huang, J., et al. Bioinformatics in MicroRNA Research. Methods in Molecular Biology, vol 1617. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7046-9_7

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  • DOI: https://doi.org/10.1007/978-1-4939-7046-9_7

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7044-5

  • Online ISBN: 978-1-4939-7046-9

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