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Computational Detection of Pre-microRNAs

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miRNomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2257))

Abstract

MicroRNA (miRNA) studies have been one of the most popular research areas in recent years. Although thousands of miRNAs have been detected in several species, the majority remains unidentified. Thus, finding novel miRNAs is a vital element for investigating miRNA mediated posttranscriptional gene regulation machineries. Furthermore, experimental methods have challenging inadequacies in their capability to detect rare miRNAs, and are also limited to the state of the organism under examination (e.g., tissue type, developmental stage, stress-disease conditions). These issues have initiated the creation of high-level computational methodologies endeavoring to distinguish potential miRNAs in silico. On the other hand, most of these tools suffer from high numbers of false positives and/or false negatives and as a result they do not provide enough confidence for validating all their predictions experimentally. In this chapter, computational difficulties in detection of pre-miRNAs are discussed and a machine learning based approach that has been designed to address these issues is reviewed.

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Author information

Authors and Affiliations

  1. Department of Bioinformatics, Faculty of Life and Natural Sciences, Abdullah Gül University, Kayseri, Turkey

    Müşerref Duygu Saçar Demirci

Authors
  1. Müşerref Duygu Saçar Demirci
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Corresponding author

Correspondence to Müşerref Duygu Saçar Demirci .

Editor information

Editors and Affiliations

  1. Medical Informatics and Bioinformatics, Institute for Measurement Engineering and Sensor Technology, Hochschule Ruhr West, University of Applied Sciences, Mülheim adR, Germany

    Jens Allmer

  2. Department of Information System, Galilee Digital Health Research Center (GDH), Zefat Academic College, Zefat, Israel

    Malik Yousef

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Saçar Demirci, M.D. (2022). Computational Detection of Pre-microRNAs. In: Allmer, J., Yousef, M. (eds) miRNomics. Methods in Molecular Biology, vol 2257. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1170-8_8

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  • DOI: https://doi.org/10.1007/978-1-0716-1170-8_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1169-2

  • Online ISBN: 978-1-0716-1170-8

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