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    A computational grid framework for immunological applications

    Halling-Brown, Mark D. and Moss, David S. and Sansom, Clare E. and Shepherd, Adrian J. (2009) A computational grid framework for immunological applications. Philosophical Transactions of the Royal Society A 367 (1898), pp. 2705-2716. ISSN 1364-503X.

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    Abstract

    We have developed a computational Grid that enables us to exploit through a single interface a range of local, national and international resources. It insulates the user as far as possible from issues concerning administrative boundaries, passwords and different operating system features. This work has been undertaken as part of the European Union ImmunoGrid project whose aim is to develop simulations of the immune system at the molecular, cellular and organ levels. The ImmunoGrid consortium has members with computational resources on both sides of the Atlantic. By making extensive use of existing Grid middleware, our Grid has enabled us to exploit consortium and publicly available computers in a unified way, notwithstanding the diverse local software and administrative environments. We took 40 000 polypeptide sequences from 4000 avian and mammalian influenza strains and used a neural network for class I T-cell epitope prediction tools for 120 class I alleles and haplotypes to generate over 14 million high-quality protein–peptide binding predictions that we are mapping onto the three-dimensional structures of the proteins. By contrast, the Grid is also being used for developing new methods for class T-cell epitope predictions, where we have running batches of 120 molecular dynamics free-energy calculations.

    Metadata

    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Natural Sciences
    Research Centres and Institutes: Bioinformatics, Bloomsbury Centre for (Closed), Structural Molecular Biology, Institute of (ISMB)
    Depositing User: Administrator
    Date Deposited: 04 Aug 2010 14:09
    Last Modified: 02 Aug 2023 16:49
    URI: https://eprints.bbk.ac.uk/id/eprint/1090

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