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Design and implementation of microarray gene expression markup language (MAGE-ML)
Authors:Spellman Paul T  Miller Michael  Stewart Jason  Troup Charles  Sarkans Ugis  Chervitz Steve  Bernhart Derek  Sherlock Gavin  Ball Catherine  Lepage Marc  Swiatek Marcin  Marks W L  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
Institution:Department of Cell and Molecular Biology, University of California at Berkeley, Berkeley, CA 94720-3206, USA. spellman@fruitfly.org
Abstract:

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.
Keywords:
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