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Computational Methods and Software Tools for Functional Analysis of miRNA Data
dc.contributor.author | García Moreno, Adrian | |
dc.contributor.author | Carmona Sáez, Pedro | |
dc.date.accessioned | 2020-11-12T09:59:51Z | |
dc.date.available | 2020-11-12T09:59:51Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Garcia-Moreno, Adrian; Carmona-Saez, Pedro. 2020. "Computational Methods and Software Tools for Functional Analysis of miRNA Data." Biomolecules 10, no. 9: 1252. [doi: 10.3390/biom10091252] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/64217 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | Junta de Andalucia PI-0173-2017 CV20.36723 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Functional analysis | es_ES |
dc.subject | miRNAs | es_ES |
dc.subject | ncRNA | es_ES |
dc.subject | Databases | es_ES |
dc.subject | Enrichment | es_ES |
dc.subject | Tools | es_ES |
dc.title | Computational Methods and Software Tools for Functional Analysis of miRNA Data | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.3390/biom10091252 |