Microarray Data Standards and Supporting Applications

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DESCRIPTION (provided by applicant): This application proposes to obtain formal funding to provide the functional genomics community with tools and resources to use standard formats and practices to communicate their data. Our group, the Microarray Gene Expression Data Society (MGED), is an international organization of biologist, computer scientists and data analysts whose aim is to promote and extend experimental science by providing the infrastructure and resources for sharing microarray and other large-scale biological data. This infrastructure includes standards for exchange and annotation of these data and supporting software that provides a common ground for the development of databases and data acquisition, management and analysis tools based on these standards. MGED resources (MIAME, MAGE-ML, MAGE-stk and the MGED Ontology) are already in widespread use, so this grant application seeks funding to improve them, develop new features and to provide dependable support to the research and computational communities using MGED resources. Each specific aim is closely tied to at least one other aim, continuing the close and collaborative work that has been the hallmark of MGED. In addition, each of the aims will require communication with the larger research community, both to obtain criticism and feedback, as well as to provide access to resources and assistance in using them. All software produced will continue to be freely available under the MIT Open Source license, and co-development by others will be facilitated by frequent software development "jamborees." We propose to extend and improve the MAGE Object Model, develop and disseminate an advanced MAGE software toolkit, research and create data quality metrics for microarray data, extend and communicate ontologies for describing microarray experiments, develop and provide tools for validating documents for MIAME compliance and MAGE formatting and to develop freely available tools that allow us to share data.