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Design and implementation of microarray gene expression markup language (MAGE-ML)

BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to...

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Autores principales: Spellman, Paul T, Miller, Michael, Stewart, Jason, Troup, Charles, Sarkans, Ugis, Chervitz, Steve, Bernhart, Derek, Sherlock, Gavin, Ball, Catherine, Lepage, Marc, Swiatek, Marcin, Marks, WL, Goncalves, Jason, Markel, Scott, Iordan, Daniel, Shojatalab, Mohammadreza, Pizarro, Angel, White, Joe, Hubley, Robert, Deutsch, Eric, Senger, Martin, Aronow, Bruce J, Robinson, Alan, Bassett, Doug, Stoeckert, Christian J, Brazma, Alvis
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2002
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC126871/
https://www.ncbi.nlm.nih.gov/pubmed/12225585
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author Spellman, Paul T
Miller, Michael
Stewart, Jason
Troup, Charles
Sarkans, Ugis
Chervitz, Steve
Bernhart, Derek
Sherlock, Gavin
Ball, Catherine
Lepage, Marc
Swiatek, Marcin
Marks, WL
Goncalves, Jason
Markel, Scott
Iordan, Daniel
Shojatalab, Mohammadreza
Pizarro, Angel
White, Joe
Hubley, Robert
Deutsch, Eric
Senger, Martin
Aronow, Bruce J
Robinson, Alan
Bassett, Doug
Stoeckert, Christian J
Brazma, Alvis
author_facet Spellman, Paul T
Miller, Michael
Stewart, Jason
Troup, Charles
Sarkans, Ugis
Chervitz, Steve
Bernhart, Derek
Sherlock, Gavin
Ball, Catherine
Lepage, Marc
Swiatek, Marcin
Marks, WL
Goncalves, Jason
Markel, Scott
Iordan, Daniel
Shojatalab, Mohammadreza
Pizarro, Angel
White, Joe
Hubley, Robert
Deutsch, Eric
Senger, Martin
Aronow, Bruce J
Robinson, Alan
Bassett, Doug
Stoeckert, Christian J
Brazma, Alvis
author_sort Spellman, Paul T
collection PubMed
description BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. RESULTS: To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.
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spelling pubmed-1268712002-10-09 Design and implementation of microarray gene expression markup language (MAGE-ML) Spellman, Paul T Miller, Michael Stewart, Jason Troup, Charles Sarkans, Ugis Chervitz, Steve Bernhart, Derek Sherlock, Gavin Ball, Catherine Lepage, Marc Swiatek, Marcin Marks, WL Goncalves, Jason Markel, Scott Iordan, Daniel Shojatalab, Mohammadreza Pizarro, Angel White, Joe Hubley, Robert Deutsch, Eric Senger, Martin Aronow, Bruce J Robinson, Alan Bassett, Doug Stoeckert, Christian J Brazma, Alvis Genome Biol Research BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. RESULTS: To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier. BioMed Central 2002 2002-08-23 /pmc/articles/PMC126871/ /pubmed/12225585 Text en Copyright © 2002 Spellman et al., licensee BioMed Central Ltd
spellingShingle Research
Spellman, Paul T
Miller, Michael
Stewart, Jason
Troup, Charles
Sarkans, Ugis
Chervitz, Steve
Bernhart, Derek
Sherlock, Gavin
Ball, Catherine
Lepage, Marc
Swiatek, Marcin
Marks, WL
Goncalves, Jason
Markel, Scott
Iordan, Daniel
Shojatalab, Mohammadreza
Pizarro, Angel
White, Joe
Hubley, Robert
Deutsch, Eric
Senger, Martin
Aronow, Bruce J
Robinson, Alan
Bassett, Doug
Stoeckert, Christian J
Brazma, Alvis
Design and implementation of microarray gene expression markup language (MAGE-ML)
title Design and implementation of microarray gene expression markup language (MAGE-ML)
title_full Design and implementation of microarray gene expression markup language (MAGE-ML)
title_fullStr Design and implementation of microarray gene expression markup language (MAGE-ML)
title_full_unstemmed Design and implementation of microarray gene expression markup language (MAGE-ML)
title_short Design and implementation of microarray gene expression markup language (MAGE-ML)
title_sort design and implementation of microarray gene expression markup language (mage-ml)
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC126871/
https://www.ncbi.nlm.nih.gov/pubmed/12225585
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