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miRGate: a curated database of human, mouse and rat miRNA–mRNA targets

MicroRNAs (miRNAs) are small non-coding elements involved in the post-transcriptional down-regulation of gene expression through base pairing with messenger RNAs (mRNAs). Through this mechanism, several miRNA–mRNA pairs have been described as critical in the regulation of multiple cellular processes...

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Detalles Bibliográficos
Autores principales: Andrés-León, Eduardo, González Peña, Daniel, Gómez-López, Gonzalo, Pisano, David G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390609/
https://www.ncbi.nlm.nih.gov/pubmed/25858286
http://dx.doi.org/10.1093/database/bav035
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author Andrés-León, Eduardo
González Peña, Daniel
Gómez-López, Gonzalo
Pisano, David G.
author_facet Andrés-León, Eduardo
González Peña, Daniel
Gómez-López, Gonzalo
Pisano, David G.
author_sort Andrés-León, Eduardo
collection PubMed
description MicroRNAs (miRNAs) are small non-coding elements involved in the post-transcriptional down-regulation of gene expression through base pairing with messenger RNAs (mRNAs). Through this mechanism, several miRNA–mRNA pairs have been described as critical in the regulation of multiple cellular processes, including early embryonic development and pathological conditions. Many of these pairs (such as miR-15 b/BCL2 in apoptosis or BART-6/BCL6 in diffuse large B-cell lymphomas) were experimentally discovered and/or computationally predicted. Available tools for target prediction are usually based on sequence matching, thermodynamics and conservation, among other approaches. Nevertheless, the main issue on miRNA–mRNA pair prediction is the little overlapping results among different prediction methods, or even with experimentally validated pairs lists, despite the fact that all rely on similar principles. To circumvent this problem, we have developed miRGate, a database containing novel computational predicted miRNA–mRNA pairs that are calculated using well-established algorithms. In addition, it includes an updated and complete dataset of sequences for both miRNA and mRNAs 3′-Untranslated region from human (including human viruses), mouse and rat, as well as experimentally validated data from four well-known databases. The underlying methodology of miRGate has been successfully applied to independent datasets providing predictions that were convincingly validated by functional assays. miRGate is an open resource available at http://mirgate.bioinfo.cnio.es. For programmatic access, we have provided a representational state transfer web service application programming interface that allows accessing the database at http://mirgate.bioinfo.cnio.es/API/ Database URL: http://mirgate.bioinfo.cnio.es
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spelling pubmed-43906092015-04-09 miRGate: a curated database of human, mouse and rat miRNA–mRNA targets Andrés-León, Eduardo González Peña, Daniel Gómez-López, Gonzalo Pisano, David G. Database (Oxford) Database Tool MicroRNAs (miRNAs) are small non-coding elements involved in the post-transcriptional down-regulation of gene expression through base pairing with messenger RNAs (mRNAs). Through this mechanism, several miRNA–mRNA pairs have been described as critical in the regulation of multiple cellular processes, including early embryonic development and pathological conditions. Many of these pairs (such as miR-15 b/BCL2 in apoptosis or BART-6/BCL6 in diffuse large B-cell lymphomas) were experimentally discovered and/or computationally predicted. Available tools for target prediction are usually based on sequence matching, thermodynamics and conservation, among other approaches. Nevertheless, the main issue on miRNA–mRNA pair prediction is the little overlapping results among different prediction methods, or even with experimentally validated pairs lists, despite the fact that all rely on similar principles. To circumvent this problem, we have developed miRGate, a database containing novel computational predicted miRNA–mRNA pairs that are calculated using well-established algorithms. In addition, it includes an updated and complete dataset of sequences for both miRNA and mRNAs 3′-Untranslated region from human (including human viruses), mouse and rat, as well as experimentally validated data from four well-known databases. The underlying methodology of miRGate has been successfully applied to independent datasets providing predictions that were convincingly validated by functional assays. miRGate is an open resource available at http://mirgate.bioinfo.cnio.es. For programmatic access, we have provided a representational state transfer web service application programming interface that allows accessing the database at http://mirgate.bioinfo.cnio.es/API/ Database URL: http://mirgate.bioinfo.cnio.es Oxford University Press 2015-04-08 /pmc/articles/PMC4390609/ /pubmed/25858286 http://dx.doi.org/10.1093/database/bav035 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Tool
Andrés-León, Eduardo
González Peña, Daniel
Gómez-López, Gonzalo
Pisano, David G.
miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title_full miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title_fullStr miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title_full_unstemmed miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title_short miRGate: a curated database of human, mouse and rat miRNA–mRNA targets
title_sort mirgate: a curated database of human, mouse and rat mirna–mrna targets
topic Database Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390609/
https://www.ncbi.nlm.nih.gov/pubmed/25858286
http://dx.doi.org/10.1093/database/bav035
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