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Computational Detection of MicroRNA Targets

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miRNomics

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

Abstract

MicroRNAs (miRNAs) are small noncoding RNAs that are recognized as posttranscriptional regulators of gene expression. These molecules have been shown to play important roles in several cellular processes. MiRNAs act on their target by guiding the RISC complex and binding to the mRNA molecule. Thus, it is recognized that the function of a miRNA is determined by the function of its target (s). By using high-throughput methodologies, novel miRNAs are being identified, but their functions remain uncharted. Target validation is crucial to properly understand the specific role of a miRNA in a cellular pathway. However, molecular techniques for experimental validation of miRNA–target interaction are expensive, time-consuming, laborious, and can be not accurate in inferring true interactions. Thus, accurate miRNA target predictions are helpful to understand the functions of miRNAs. There are several algorithms proposed for target prediction and databases containing miRNA-target information. However, these available computational tools for prediction still generate a large number of false positives and fail to detect a considerable number of true targets, which indicates the necessity of highly confident approaches to identify bona fide miRNA–target interactions. This chapter focuses on tools and strategies used for miRNA target prediction, by providing practical insights and outlooks.

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Acknowledgments

This work was supported by grants from São Paulo Research Foundation (FAPESP - processes numbers: 2013/06864-7; 2018/26520-4), CAPES (process number 88887.177457/2018-00), and The Brazilian National Council for Scientific and Technological Development (CNPq—process number 167444/2017-4).

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Authors and Affiliations

  1. Laboratório Especial de Toxinologia Aplicada, CeTICS, Instituto Butantan, São Paulo, SP, Brazil

    Pedro Gabriel Nachtigall

  2. Department of Morphology, Institute of Biosciences of Botucatu (IBB), São Paulo State University (UNESP), Botucatu, Brazil

    Luiz Augusto Bovolenta

Authors
  1. Pedro Gabriel Nachtigall
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  2. Luiz Augusto Bovolenta
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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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Nachtigall, P.G., Bovolenta, L.A. (2022). Computational Detection of MicroRNA Targets. 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_10

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  • DOI: https://doi.org/10.1007/978-1-0716-1170-8_10

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1169-2

  • Online ISBN: 978-1-0716-1170-8

  • eBook Packages: Springer Protocols

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