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

Authors :
Ugis Sarkans
Robert Hubley
Bruce J. Aronow
Doug Bassett
Alan J. Robinson
Scott Markel
Jason E. Stewart
Alvis Brazma
Steve Chervitz
Christian J. Stoeckert
Derek Bernhart
Martin Senger
Daniel Iordan
WL Marks
Angel Pizarro
Marcin Swiatek
Joseph White
Jason Goncalves
Paul T. Spellman
Charles Troup
Marc Lepage
Gavin Sherlock
Catherine A. Ball
Eric W. Deutsch
Michael W. Miller
Mohammadreza Shojatalab
Source :
Genome Biology, Europe PubMed Central
Publication Year :
2002
Publisher :
BioMed Central, 2002.

Abstract

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. 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.<br />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.

Details

Language :
English
ISSN :
14656914 and 14656906
Volume :
3
Issue :
9
Database :
OpenAIRE
Journal :
Genome Biology
Accession number :
edsair.doi.dedup.....530ada04a2e267bab229d266f075783a