Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experime...

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Autores principales:	Andrés Rincón-Riveros, Duvan Morales, Josefa Antonia Rodríguez, Victoria E. Villegas, Liliana López-Kleine
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	genomics transcriptome ncRNA lncRNA interactome bioinformatics Biology (General) QH301-705.5 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/5191354e368a4246a3cb516bdff43fce
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spelling	oai:doaj.org-article:5191354e368a4246a3cb516bdff43fce2021-11-11T16:52:32ZBioinformatic Tools for the Analysis and Prediction of ncRNA Interactions10.3390/ijms2221113971422-00671661-6596https://doaj.org/article/5191354e368a4246a3cb516bdff43fce2021-10-01T00:00:00Zhttps://www.mdpi.com/1422-0067/22/21/11397https://doaj.org/toc/1661-6596https://doaj.org/toc/1422-0067Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.Andrés Rincón-RiverosDuvan MoralesJosefa Antonia RodríguezVictoria E. VillegasLiliana López-KleineMDPI AGarticlegenomicstranscriptomencRNAlncRNAinteractomebioinformaticsBiology (General)QH301-705.5ChemistryQD1-999ENInternational Journal of Molecular Sciences, Vol 22, Iss 11397, p 11397 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	genomics transcriptome ncRNA lncRNA interactome bioinformatics Biology (General) QH301-705.5 Chemistry QD1-999
spellingShingle	genomics transcriptome ncRNA lncRNA interactome bioinformatics Biology (General) QH301-705.5 Chemistry QD1-999 Andrés Rincón-Riveros Duvan Morales Josefa Antonia Rodríguez Victoria E. Villegas Liliana López-Kleine Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
description	Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.
format	article
author	Andrés Rincón-Riveros Duvan Morales Josefa Antonia Rodríguez Victoria E. Villegas Liliana López-Kleine
author_facet	Andrés Rincón-Riveros Duvan Morales Josefa Antonia Rodríguez Victoria E. Villegas Liliana López-Kleine
author_sort	Andrés Rincón-Riveros
title	Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
title_short	Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
title_full	Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
title_fullStr	Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
title_full_unstemmed	Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions
title_sort	bioinformatic tools for the analysis and prediction of ncrna interactions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5191354e368a4246a3cb516bdff43fce
work_keys_str_mv	AT andresrinconriveros bioinformatictoolsfortheanalysisandpredictionofncrnainteractions AT duvanmorales bioinformatictoolsfortheanalysisandpredictionofncrnainteractions AT josefaantoniarodriguez bioinformatictoolsfortheanalysisandpredictionofncrnainteractions AT victoriaevillegas bioinformatictoolsfortheanalysisandpredictionofncrnainteractions AT lilianalopezkleine bioinformatictoolsfortheanalysisandpredictionofncrnainteractions
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Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

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