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miRNAFold: a web server for fast miRNA precursor prediction in genomes

Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In par...

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Detalles Bibliográficos
Autores principales: Tav, Christophe, Tempel, Sébastien, Poligny, Laurent, Tahi, Fariza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987958/
https://www.ncbi.nlm.nih.gov/pubmed/27242364
http://dx.doi.org/10.1093/nar/gkw459
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author Tav, Christophe
Tempel, Sébastien
Poligny, Laurent
Tahi, Fariza
author_facet Tav, Christophe
Tempel, Sébastien
Poligny, Laurent
Tahi, Fariza
author_sort Tav, Christophe
collection PubMed
description Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold.
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spelling pubmed-49879582016-08-22 miRNAFold: a web server for fast miRNA precursor prediction in genomes Tav, Christophe Tempel, Sébastien Poligny, Laurent Tahi, Fariza Nucleic Acids Res Web Server issue Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold. Oxford University Press 2016-07-08 2016-05-29 /pmc/articles/PMC4987958/ /pubmed/27242364 http://dx.doi.org/10.1093/nar/gkw459 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server issue
Tav, Christophe
Tempel, Sébastien
Poligny, Laurent
Tahi, Fariza
miRNAFold: a web server for fast miRNA precursor prediction in genomes
title miRNAFold: a web server for fast miRNA precursor prediction in genomes
title_full miRNAFold: a web server for fast miRNA precursor prediction in genomes
title_fullStr miRNAFold: a web server for fast miRNA precursor prediction in genomes
title_full_unstemmed miRNAFold: a web server for fast miRNA precursor prediction in genomes
title_short miRNAFold: a web server for fast miRNA precursor prediction in genomes
title_sort mirnafold: a web server for fast mirna precursor prediction in genomes
topic Web Server issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987958/
https://www.ncbi.nlm.nih.gov/pubmed/27242364
http://dx.doi.org/10.1093/nar/gkw459
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