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miRror-Suite: decoding coordinated regulation by microRNAs

MicroRNAs (miRNAs) are short, non-coding RNAs that negatively regulate post-transcriptional mRNA levels. Recent data from cross-linking and immunoprecipitation technologies confirmed the combinatorial nature of the miRNA regulation. We present the miRror-Suite platform, developed to yield a robust a...

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Detalles Bibliográficos
Autores principales: Friedman, Yitzhak, Karsenty, Solange, Linial, Michal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051442/
https://www.ncbi.nlm.nih.gov/pubmed/24907353
http://dx.doi.org/10.1093/database/bau043
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author Friedman, Yitzhak
Karsenty, Solange
Linial, Michal
author_facet Friedman, Yitzhak
Karsenty, Solange
Linial, Michal
author_sort Friedman, Yitzhak
collection PubMed
description MicroRNAs (miRNAs) are short, non-coding RNAs that negatively regulate post-transcriptional mRNA levels. Recent data from cross-linking and immunoprecipitation technologies confirmed the combinatorial nature of the miRNA regulation. We present the miRror-Suite platform, developed to yield a robust and concise explanation for miRNA regulation from a large collection of differentially expressed transcripts and miRNAs. The miRror-Suite platform includes the miRror2.0 and Probability Supported Iterative miRror (PSI-miRror) tools. Researchers who performed large-scale transcriptomics or miRNA profiling experiments from cells and tissues will benefit from miRror-Suite. Our platform provides a concise, plausible explanation for the regulation of miRNAs in such complex settings. The input for miRror2.0 may include hundreds of differentially expressed genes or miRNAs. In the case of miRNAs as input, the algorithm seeks the statistically most likely set of genes regulated by this input. Alternatively, for a set of genes, the miRror algorithm seeks a collection of miRNAs that best explains their regulation. The miRror-Suite algorithm designates statistical criteria that were uniformly applied to a dozen miRNA-target prediction databases. Users select the preferred databases for predictions and numerous optional filters/parameters that restrict the search to the desired tissues, cell lines, level of expression and predictor scores. PSI-miRror is an advanced application for refining the input set by gradually enhancing the degree of pairing of the sets of miRNAs with the sets of targets. The iterations of PSI-miRror probe the interlinked nature of miRNAs and targets within cells. miRror-Suite serves experimentalists in facilitating the understanding of miRNA regulation through combinatorial– cooperative activity. The platform applies to human, mouse, rat, fly, worm and zebrafish. Database URL: http://www.mirrorsuite.cs.huji.ac.il.
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spelling pubmed-40514422014-06-12 miRror-Suite: decoding coordinated regulation by microRNAs Friedman, Yitzhak Karsenty, Solange Linial, Michal Database (Oxford) Original Article MicroRNAs (miRNAs) are short, non-coding RNAs that negatively regulate post-transcriptional mRNA levels. Recent data from cross-linking and immunoprecipitation technologies confirmed the combinatorial nature of the miRNA regulation. We present the miRror-Suite platform, developed to yield a robust and concise explanation for miRNA regulation from a large collection of differentially expressed transcripts and miRNAs. The miRror-Suite platform includes the miRror2.0 and Probability Supported Iterative miRror (PSI-miRror) tools. Researchers who performed large-scale transcriptomics or miRNA profiling experiments from cells and tissues will benefit from miRror-Suite. Our platform provides a concise, plausible explanation for the regulation of miRNAs in such complex settings. The input for miRror2.0 may include hundreds of differentially expressed genes or miRNAs. In the case of miRNAs as input, the algorithm seeks the statistically most likely set of genes regulated by this input. Alternatively, for a set of genes, the miRror algorithm seeks a collection of miRNAs that best explains their regulation. The miRror-Suite algorithm designates statistical criteria that were uniformly applied to a dozen miRNA-target prediction databases. Users select the preferred databases for predictions and numerous optional filters/parameters that restrict the search to the desired tissues, cell lines, level of expression and predictor scores. PSI-miRror is an advanced application for refining the input set by gradually enhancing the degree of pairing of the sets of miRNAs with the sets of targets. The iterations of PSI-miRror probe the interlinked nature of miRNAs and targets within cells. miRror-Suite serves experimentalists in facilitating the understanding of miRNA regulation through combinatorial– cooperative activity. The platform applies to human, mouse, rat, fly, worm and zebrafish. Database URL: http://www.mirrorsuite.cs.huji.ac.il. Oxford University Press 2014-06-06 /pmc/articles/PMC4051442/ /pubmed/24907353 http://dx.doi.org/10.1093/database/bau043 Text en © The Author(s) 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Friedman, Yitzhak
Karsenty, Solange
Linial, Michal
miRror-Suite: decoding coordinated regulation by microRNAs
title miRror-Suite: decoding coordinated regulation by microRNAs
title_full miRror-Suite: decoding coordinated regulation by microRNAs
title_fullStr miRror-Suite: decoding coordinated regulation by microRNAs
title_full_unstemmed miRror-Suite: decoding coordinated regulation by microRNAs
title_short miRror-Suite: decoding coordinated regulation by microRNAs
title_sort mirror-suite: decoding coordinated regulation by micrornas
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051442/
https://www.ncbi.nlm.nih.gov/pubmed/24907353
http://dx.doi.org/10.1093/database/bau043
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