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JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
Enabling GeneHunter as a grid service: a case study for implementing analytical services in biomedical grids.
BACKGROUND: A cursory analysis of the biomedical grid literature shows that most projects emphasize data sharing and the development of new applications for the grid environment. Much less is known about the best practices for the migration of existing analytical tools into the grid environment.
OBJECTIVES: To make GeneHunter available as a grid service and to evaluate the effort and best practices needed to enable a legacy application as a grid service when addressing semantic integration and using the caBIG tools.
METHODS: We used the tools available in the caBIG environment because these tools are quite general and they may be used to deploy services in similar biomedical grids that are OGSA-compliant.
RESULTS: We achieved semantic integration of GeneHunter within the caBIG by creating a new UML model, LinkageX, for the LINKAGE data format. The LinkageX UML model has been published in the caDSR and it is publically available for usage with GeneHunter or any other program using this data format.
CONCLUSIONS: While achieving semantic interoperability is still a time-consuming task, the tools available in caBIG can greatly enhance productivity and decrease errors.
OBJECTIVES: To make GeneHunter available as a grid service and to evaluate the effort and best practices needed to enable a legacy application as a grid service when addressing semantic integration and using the caBIG tools.
METHODS: We used the tools available in the caBIG environment because these tools are quite general and they may be used to deploy services in similar biomedical grids that are OGSA-compliant.
RESULTS: We achieved semantic integration of GeneHunter within the caBIG by creating a new UML model, LinkageX, for the LINKAGE data format. The LinkageX UML model has been published in the caDSR and it is publically available for usage with GeneHunter or any other program using this data format.
CONCLUSIONS: While achieving semantic interoperability is still a time-consuming task, the tools available in caBIG can greatly enhance productivity and decrease errors.
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