Using BioMart as a framework to manage and query pancreatic cancer data

We describe the Pancreatic Expression Database (PED), the first cancer database originally designed based on the BioMart infrastructure. The PED portal brings together multidimensional pancreatic cancer data from the literature including genomic, proteomic, miRNA and gene expression profiles. Based...

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Detalles Bibliográficos
Autores principales: Cutts, Rosalind J., Gadaleta, Emanuela, Lemoine, Nicholas R., Chelala, Claude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3114646/
https://www.ncbi.nlm.nih.gov/pubmed/21666272
http://dx.doi.org/10.1093/database/bar024
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author Cutts, Rosalind J.
Gadaleta, Emanuela
Lemoine, Nicholas R.
Chelala, Claude
author_facet Cutts, Rosalind J.
Gadaleta, Emanuela
Lemoine, Nicholas R.
Chelala, Claude
author_sort Cutts, Rosalind J.
collection PubMed
description We describe the Pancreatic Expression Database (PED), the first cancer database originally designed based on the BioMart infrastructure. The PED portal brings together multidimensional pancreatic cancer data from the literature including genomic, proteomic, miRNA and gene expression profiles. Based on the BioMart 0.7 framework, the database is easily integrated with other BioMart-compliant resources, such as Ensembl and Reactome, to give access to a wide range of annotations alongside detailed experimental conditions. This article is intended to give an overview of PED, describe its data content and work through examples of how to successfully mine and integrate pancreatic cancer data sets and other BioMart resources. Database URL: http://www.pancreasexpression.org
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spelling pubmed-31146462011-06-15 Using BioMart as a framework to manage and query pancreatic cancer data Cutts, Rosalind J. Gadaleta, Emanuela Lemoine, Nicholas R. Chelala, Claude Database (Oxford) Original Article We describe the Pancreatic Expression Database (PED), the first cancer database originally designed based on the BioMart infrastructure. The PED portal brings together multidimensional pancreatic cancer data from the literature including genomic, proteomic, miRNA and gene expression profiles. Based on the BioMart 0.7 framework, the database is easily integrated with other BioMart-compliant resources, such as Ensembl and Reactome, to give access to a wide range of annotations alongside detailed experimental conditions. This article is intended to give an overview of PED, describe its data content and work through examples of how to successfully mine and integrate pancreatic cancer data sets and other BioMart resources. Database URL: http://www.pancreasexpression.org Oxford University Press 2011-06-11 /pmc/articles/PMC3114646/ /pubmed/21666272 http://dx.doi.org/10.1093/database/bar024 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Cutts, Rosalind J.
Gadaleta, Emanuela
Lemoine, Nicholas R.
Chelala, Claude
Using BioMart as a framework to manage and query pancreatic cancer data
title Using BioMart as a framework to manage and query pancreatic cancer data
title_full Using BioMart as a framework to manage and query pancreatic cancer data
title_fullStr Using BioMart as a framework to manage and query pancreatic cancer data
title_full_unstemmed Using BioMart as a framework to manage and query pancreatic cancer data
title_short Using BioMart as a framework to manage and query pancreatic cancer data
title_sort using biomart as a framework to manage and query pancreatic cancer data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3114646/
https://www.ncbi.nlm.nih.gov/pubmed/21666272
http://dx.doi.org/10.1093/database/bar024
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