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miRNomics: MicroRNA Biology and Computational Analysis pp 177–187Cite as

Machine Learning Methods for MicroRNA Gene Prediction

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1107))

Abstract

MicroRNAs (miRNAs) are single-stranded, small, noncoding RNAs of about 22 nucleotides in length, which control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, or destabilization of their target mRNAs. Although hundreds of miRNAs have been identified in various species, many more may still remain unknown. Therefore, discovery of new miRNA genes is an important step for understanding miRNA-mediated posttranscriptional regulation mechanisms. It seems that biological approaches to identify miRNA genes might be limited in their ability to detect rare miRNAs and are further limited to the tissues examined and the developmental stage of the organism under examination. These limitations have led to the development of sophisticated computational approaches attempting to identify possible miRNAs in silico. In this chapter, we discuss computational problems in miRNA prediction studies and review some of the many machine learning methods that have been tried to address the issues.

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Acknowledgements

This study was in part supported by an award received from the Turkish Academy of Sciences for outstanding young scientists (TUBA GEBIP, http://www.tuba.gov.tr).

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Authors and Affiliations

  1. Molecular Biology and Genetics, Izmir Institute of Technology, Izmir, Turkey

    Müşerref Duygu Saçar & Jens Allmer

Authors
  1. Müşerref Duygu Saçar
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  2. Jens Allmer
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Editors and Affiliations

  1. Dabburiya Village, Israel

    Malik Yousef

  2. Izmir Institute of Technology, Izmir, Turkey

    Jens Allmer

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Saçar, M.D., Allmer, J. (2014). Machine Learning Methods for MicroRNA Gene Prediction. In: Yousef, M., Allmer, J. (eds) miRNomics: MicroRNA Biology and Computational Analysis. Methods in Molecular Biology, vol 1107. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-748-8_10

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  • DOI: https://doi.org/10.1007/978-1-62703-748-8_10

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-747-1

  • Online ISBN: 978-1-62703-748-8

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