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Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions

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Bioinformatics in MicroRNA Research

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

Abstract

In recent years, the role of miRNAs in post-transcriptional gene regulation has provided new insights into the understanding of several types of cancers and neurological disorders. Although miRNA research has gathered great momentum since its discovery, traditional biological methods for finding miRNA genes and targets continue to remain a huge challenge due to the laborious tasks and extensive time involved. Fortunately, advances in computational methods have yielded considerable improvements in miRNA studies. This literature review briefly discusses recent machine learning-based techniques applied in the discovery of miRNAs, prediction of miRNA targets, and inference of miRNA functions. We also discuss the limitations of how these approaches have been elucidated in previous studies.

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Author information

Authors and Affiliations

  1. School of Computer Science and Mathematics, University of Central Missouri, Warrensburg, MO, 64093, USA

    Sumi Singh & Anshuman Singh

  2. Department of Computer Science, University of South Alabama School of Computing, Shelby Hall, Suite 2101, 150 Jaguar Drive, Mobile, AL, 36688, USA

    Ryan G. Benton Ph.D.

  3. Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA, 70503, USA

    Anurag Singh

Authors
  1. Sumi Singh
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  2. Ryan G. Benton Ph.D.
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  3. Anurag Singh
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  4. Anshuman Singh
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Corresponding author

Correspondence to Ryan G. Benton 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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Singh, S., Benton, R.G., Singh, A., Singh, A. (2017). Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions. 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_16

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  • DOI: https://doi.org/10.1007/978-1-4939-7046-9_16

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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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