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An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis

BACKGROUND: In spite of two-dimensional gel electrophoresis (2-DE) being an effective and widely used method to screen the proteome, its data standardization has still not matured to the level of microarray genomics data or mass spectrometry approaches. The trend toward identifying encompassing data...

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Autores principales: Stanislaus, Romesh, Arthur, John M, Rajagopalan, Balaji, Moerschell, Rick, McGlothlen, Brian, Almeida, Jonas S
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2231339/
https://www.ncbi.nlm.nih.gov/pubmed/18179696
http://dx.doi.org/10.1186/1471-2105-9-4
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author Stanislaus, Romesh
Arthur, John M
Rajagopalan, Balaji
Moerschell, Rick
McGlothlen, Brian
Almeida, Jonas S
author_facet Stanislaus, Romesh
Arthur, John M
Rajagopalan, Balaji
Moerschell, Rick
McGlothlen, Brian
Almeida, Jonas S
author_sort Stanislaus, Romesh
collection PubMed
description BACKGROUND: In spite of two-dimensional gel electrophoresis (2-DE) being an effective and widely used method to screen the proteome, its data standardization has still not matured to the level of microarray genomics data or mass spectrometry approaches. The trend toward identifying encompassing data standards has been expanding from genomics to transcriptomics, and more recently to proteomics. The relative success of genomic and transcriptomic data standardization has enabled the development of central repositories such as GenBank and Gene Expression Omnibus. An equivalent 2-DE-centric data structure would similarly have to include a balance among raw data, basic feature detection results, sufficiency in the description of the experimental context and methods, and an overall structure that facilitates a diversity of usages, from central reposition to local data representation in LIMs systems. RESULTS & CONCLUSION: Achieving such a balance can only be accomplished through several iterations involving bioinformaticians, bench molecular biologists, and the manufacturers of the equipment and commercial software from which the data is primarily generated. Such an encompassing data structure is described here, developed as the mature successor to the well established and broadly used earlier version. A public repository, AGML Central, is configured with a suite of tools for the conversion from a variety of popular formats, web-based visualization, and interoperation with other tools and repositories, and is particularly mass-spectrometry oriented with I/O for annotation and data analysis.
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spelling pubmed-22313392008-02-06 An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis Stanislaus, Romesh Arthur, John M Rajagopalan, Balaji Moerschell, Rick McGlothlen, Brian Almeida, Jonas S BMC Bioinformatics Research Article BACKGROUND: In spite of two-dimensional gel electrophoresis (2-DE) being an effective and widely used method to screen the proteome, its data standardization has still not matured to the level of microarray genomics data or mass spectrometry approaches. The trend toward identifying encompassing data standards has been expanding from genomics to transcriptomics, and more recently to proteomics. The relative success of genomic and transcriptomic data standardization has enabled the development of central repositories such as GenBank and Gene Expression Omnibus. An equivalent 2-DE-centric data structure would similarly have to include a balance among raw data, basic feature detection results, sufficiency in the description of the experimental context and methods, and an overall structure that facilitates a diversity of usages, from central reposition to local data representation in LIMs systems. RESULTS & CONCLUSION: Achieving such a balance can only be accomplished through several iterations involving bioinformaticians, bench molecular biologists, and the manufacturers of the equipment and commercial software from which the data is primarily generated. Such an encompassing data structure is described here, developed as the mature successor to the well established and broadly used earlier version. A public repository, AGML Central, is configured with a suite of tools for the conversion from a variety of popular formats, web-based visualization, and interoperation with other tools and repositories, and is particularly mass-spectrometry oriented with I/O for annotation and data analysis. BioMed Central 2008-01-07 /pmc/articles/PMC2231339/ /pubmed/18179696 http://dx.doi.org/10.1186/1471-2105-9-4 Text en Copyright © 2008 Stanislaus et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Stanislaus, Romesh
Arthur, John M
Rajagopalan, Balaji
Moerschell, Rick
McGlothlen, Brian
Almeida, Jonas S
An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title_full An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title_fullStr An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title_full_unstemmed An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title_short An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis
title_sort open-source representation for 2-de-centric proteomics and support infrastructure for data storage and analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2231339/
https://www.ncbi.nlm.nih.gov/pubmed/18179696
http://dx.doi.org/10.1186/1471-2105-9-4
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