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MicroRNA–Target Identification: A Combinatorial In Silico Approach

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MicroRNA Detection and Target Identification

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2630))

Abstract

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA–target prediction.

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Acknowledgements

This research was supported by a QUT postgraduate scholarship to KMTA.

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Authors and Affiliations

  1. Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), Kelvin Grove, QLD, Australia

    K. M. Taufiqul Arif, Rachel K. Okolicsanyi, Larisa M. Haupt & Lyn R. Griffiths

Authors
  1. K. M. Taufiqul Arif
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  2. Rachel K. Okolicsanyi
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  3. Larisa M. Haupt
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  4. Lyn R. Griffiths
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Corresponding author

Correspondence to Lyn R. Griffiths .

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Editors and Affiliations

  1. RNA Biology, University of East Anglia, Norwich, UK

    Tamas Dalmay

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Arif, K.M.T., Okolicsanyi, R.K., Haupt, L.M., Griffiths, L.R. (2023). MicroRNA–Target Identification: A Combinatorial In Silico Approach. In: Dalmay, T. (eds) MicroRNA Detection and Target Identification. Methods in Molecular Biology, vol 2630. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2982-6_14

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  • DOI: https://doi.org/10.1007/978-1-0716-2982-6_14

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2981-9

  • Online ISBN: 978-1-0716-2982-6

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