1. Design and implementation of microarray gene expression markup language (MAGE-ML)
- Author
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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, and Mohammadreza Shojatalab
- Subjects
Markup language ,Microarray ,business.industry ,Minimum information about a microarray experiment ,Microarray analysis techniques ,Research ,Gene Expression Profiling ,Database schema ,Computational biology ,Sequence Analysis, DNA ,Biology ,computer.software_genre ,Models, Biological ,Gene expression profiling ,Microarray gene expression ,Microarray databases ,Computer Simulation ,Programming Languages ,Artificial intelligence ,business ,computer ,Natural language processing ,Oligonucleotide Array Sequence Analysis - 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., 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.
- Published
- 2002