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MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes

Summary: The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gen...

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Detalles Bibliográficos
Autores principales: Huerta, Mario, Munyi, Marc, Expósito, David, Querol, Enric, Cedano, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058934/
https://www.ncbi.nlm.nih.gov/pubmed/24574116
http://dx.doi.org/10.1093/bioinformatics/btu109
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author Huerta, Mario
Munyi, Marc
Expósito, David
Querol, Enric
Cedano, Juan
author_facet Huerta, Mario
Munyi, Marc
Expósito, David
Querol, Enric
Cedano, Juan
author_sort Huerta, Mario
collection PubMed
description Summary: The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Availability: Marker-gene database tool: http://ibb.uab.es/mgdb Contact: jcedano@unorte.edu.uy
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spelling pubmed-40589342014-06-18 MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes Huerta, Mario Munyi, Marc Expósito, David Querol, Enric Cedano, Juan Bioinformatics Applications Notes Summary: The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Availability: Marker-gene database tool: http://ibb.uab.es/mgdb Contact: jcedano@unorte.edu.uy Oxford University Press 2014-06-15 2013-02-25 /pmc/articles/PMC4058934/ /pubmed/24574116 http://dx.doi.org/10.1093/bioinformatics/btu109 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), 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 Applications Notes
Huerta, Mario
Munyi, Marc
Expósito, David
Querol, Enric
Cedano, Juan
MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title_full MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title_fullStr MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title_full_unstemmed MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title_short MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
title_sort mgdb: crossing the marker genes of a user microarray with a database of public-microarrays marker genes
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058934/
https://www.ncbi.nlm.nih.gov/pubmed/24574116
http://dx.doi.org/10.1093/bioinformatics/btu109
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