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

  • Sumi Singh
  • Ryan G. BentonEmail author
  • Anurag Singh
  • Anshuman Singh
Part of the Methods in Molecular Biology book series (MIMB, volume 1617)


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.

Key words

MicroRNA mRNA Target prediction Machine learning Data mining miRNA target prediction miRNA gene identification miRNA regulatory network modules MRMs Functional miRNA-mRNA regulatory modules MRMs miRNA functional annotation 


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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Sumi Singh
    • 1
  • Ryan G. Benton
    • 2
    Email author
  • Anurag Singh
    • 3
  • Anshuman Singh
    • 1
  1. 1.School of Computer Science and MathematicsUniversity of Central MissouriWarrensburgUSA
  2. 2.Department of Computer ScienceUniversity of South Alabama School of ComputingMobileUSA
  3. 3.Center for Advanced Computer StudiesUniversity of Louisiana at LafayetteLafayetteUSA

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