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    Towards the integration of mouse databases - definition and implementation of solutions to two use-cases in mouse functional genomics

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    Authors
    Gruenberger, Michael
    Alberts, Rudi
    Smedley, Damian
    Swertz, Morris
    Schofield, Paul
    Schughart, Klaus
    Issue Date
    2010-01-22
    
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    Abstract
    Abstract Background The integration of information present in many disparate biological databases represents a major challenge in biomedical research. To define the problems and needs, and to explore strategies for database integration in mouse functional genomics, we consulted the biologist user community and implemented solutions to two user-defined use-cases. Results We organised workshops, meetings and used a questionnaire to identify the needs of biologist database users in mouse functional genomics. As a result, two use-cases were developed that can be used to drive future designs or extensions of mouse databases. Here, we present the use-cases and describe some initial computational solutions for them. The application for the gene-centric use-case, "MUSIG-Gen" starts from a list of gene names and collects a wide range of data types from several distributed databases in a "shopping cart"-like manner. The iterative user-driven approach is a response to strongly articulated requests from users, especially those without computational biology backgrounds. The application for the phenotype-centric use-case, "MUSIG-Phen", is based on a similar concept and starting from phenotype descriptions retrieves information for associated genes. Conclusion The use-cases created, and their prototype software implementations should help to better define biologists' needs for database integration and may serve as a starting point for future bioinformatics solutions aimed at end-user biologists.
    Citation
    BMC Research Notes. 2010 Jan 22;3(1):16
    URI
    http://dx.doi.org/10.1186/1756-0500-3-16
    http://hdl.handle.net/10033/620698
    Type
    Journal Article
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    publications of the research group infection genetics (INFG)

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