miRNA Target Prediction: An Overview of the Past and Current Tools.

Authors

Sebastiano Di Bella, Francesco Orilio, Giovanni Nigita, Matilde Todaro, Giorgio Stassi

Published in

Methods in molecular biology (Clifton, N.J.). Volume 3056. Pages 1-19.

Abstract

MicroRNAs (miRNAs) are among the most studied molecules in recent years, and since their discovery, many miRNAs have been identified across various species. As members of the non-coding RNA family, miRNAs are key players in post-transcriptional gene regulation. These molecules can inhibit translation or promote degradation of messenger RNA (mRNA) by binding to the 3' untranslated region (UTR) of mRNA, thereby influencing almost all biological processes. To identify a miRNA's biological role, it is essential to predict the target sites to which it binds, a goal made possible through bioinformatics tools. This chapter discusses the bioinformatics tools commonly used for this purpose. Also, it analyzes the main factors considered in target prediction, such as seed match, free energy, conservation, site accessibility, multiple binding site contribution, and machine learning and deep learning approaches. Understanding the principles underlying these predictive methodologies is crucial for advancing one's biological research on miRNAs.

PMID:
42681317
Bibliographic data and abstract were imported from PubMed on 15 Oct 2026.

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