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Review

Computational Methods and Software Tools for Functional Analysis of miRNA Data

1
Bioinformatics Unit, Centre for Genomics and Oncological Research (GENyO)—Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain
2
Department of Statistics, University of Granada, 18071 Granada, Spain
*
Author to whom correspondence should be addressed.
Biomolecules 2020, 10(9), 1252; https://doi.org/10.3390/biom10091252
Received: 31 July 2020 / Revised: 24 August 2020 / Accepted: 26 August 2020 / Published: 28 August 2020
(This article belongs to the Special Issue Bioinformatics Resource and Protocols for Small RNA Research)
miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs. View Full-Text
Keywords: functional analysis; miRNA; ncRNA; databases; enrichment; tools functional analysis; miRNA; ncRNA; databases; enrichment; tools
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MDPI and ACS Style

Garcia-Moreno, A.; Carmona-Saez, P. Computational Methods and Software Tools for Functional Analysis of miRNA Data. Biomolecules 2020, 10, 1252. https://doi.org/10.3390/biom10091252

AMA Style

Garcia-Moreno A, Carmona-Saez P. Computational Methods and Software Tools for Functional Analysis of miRNA Data. Biomolecules. 2020; 10(9):1252. https://doi.org/10.3390/biom10091252

Chicago/Turabian Style

Garcia-Moreno, Adrian, and Pedro Carmona-Saez. 2020. "Computational Methods and Software Tools for Functional Analysis of miRNA Data" Biomolecules 10, no. 9: 1252. https://doi.org/10.3390/biom10091252

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