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    Data access and integration in the ISPIDER proteomics grid

    Zamboulis, Lucas and Fan, Hao and Belhajjame, Khalid and Siepen, Jennifer and Jones, Andrew and Martin, Nigel and Poulovassilis, Alexandra and Hubbard, Simon and Embury, Suzanne and Paton, Norman (2006) Data access and integration in the ISPIDER proteomics grid. In: Leser, U. and Naumann, F. and Eckman, B. (eds.) Data Integration in the Life Sciences. Lecture Notes in Computer Science 4075. Berlin, Germany: Springer, pp. 3-18. ISBN 9783540365938.

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    Abstract

    Grid computing has great potential for supporting the integration of complex, fast changing biological data repositories to enable distributed data analysis. One scenario where Grid computing has such potential is provided by proteomics resources which are rapidly being developed with the emergence of affordable, reliable methods to study the proteome. The protein identifications arising from these methods derive from multiple repositories which need to be integrated to enable uniform access to them. A number of technologies exist which enable these resources to be accessed in a Grid environment, but the independent development of these resources means that significant data integration challenges, such as heterogeneity and schema evolution, have to be met. This paper presents an architecture which supports the combined use of Grid data access (OGSA-DAI), Grid distributed querying (OGSA-DQP) and data integration (AutoMed) software tools to support distributed data analysis. We discuss the application of this architecture for the integration of several autonomous proteomics data resources.

    Metadata

    Item Type: Book Section
    Additional Information: The final publication is available at link.springer.com
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Innovation Management Research, Birkbeck Centre for, Bioinformatics, Bloomsbury Centre for (Closed), Structural Molecular Biology, Institute of (ISMB), Birkbeck Knowledge Lab
    Depositing User: Nigel Martin
    Date Deposited: 26 Feb 2014 11:46
    Last Modified: 09 Aug 2023 12:34
    URI: https://eprints.bbk.ac.uk/id/eprint/9251

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