Abstract
According to the virtual physiological human paradigm, integration is often\break required among different levels and disciplines. Large, distributed and heterogeneous repositories, as well as computationally demanding analysis tools, are more and more involved in biomedical studies. Both for storage of distributed biomedical data and metadata and for access to distributed analysis tools, a Grid-based approach may provide a shared, standardized and reliable solution. To make users able to easily access available services and data, a Grid portal has been implemented in order to hide the complexity of the framework. The portal is intended to act as Grid services provider and as Web interface for managing workflow enactment and management on the Grid. Workflows may be submitted as Grid jobs through a service-based workflow engine and monitored during execution. As a first case study for testing workflow functionalities of the Grid portal, an application is presented for the search and analysis of microarray data.
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References
Alfieri R, Barbera R, Belluomo P, Cavalli A, Cecchini R, Chierici A, Fiaschini V, Dell’Agnello L, Donno F, Ferro E. “The INFN-Grid testbed”, Future Gen. Comput. Syst. 2005, 21(2)249–258.
Andronico A, Barbera R, Falzone A, Kunszt P, Re GL, Pulvirenti A, Rodolico A. “Genius: a simple and easy way to access computational and data grids”, Future Gen. Comput. Syst. 2003, 19(6)805–813.
Gil Y, Deelman E, Blythe J, Kessleman C, Tangmunarunkit H, “Artificial intelligence and grids: workflow planning and beyond”, IEEE Intell. Syst. special issue on e-science 2004, 19(1)26–33.
Glatard T, Montagnat J, Pennac X. “MOTEUR grid-enabled data-intensive workflowmanager”, Proc. Healthgrid 2006, Valencia, Spain, June 7–9, 2006.
Li C, Wong WH. “Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection”, Proc. Natl.Acad. Sci. USA 2001, 98:31–36.
Maurer M, Molidor R, Sturn A, Hartler J, Hackl H, Stocker G, Prokesch A, Scheideler M, Trajanoski Z. “MARS: microarray analysis, retrieval, and storage system”, BMC Bioinform. 2005, 6(1): 101.
Muggleton SH. “2020 computing: exceeding human limits” Commentary, Nature,22 March 2006, 440: 409–410.
Pawitan Y, Bjöhle J, Amler L, Borg AL, Egyhazi S, Hall P, Han X, Holmberg L, Huang F, Klaar S, Liu ET, Miller L, Nordgren H, Ploner A, Sandelin K, Shaw PM, Smeds J, Skoog L, Wedrén S, Bergh J. “Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts”, Breast Cancer Res. 2005, 7(6): R953–64.
Porro I, Torterolo L, Corradi L, Fato M, Papadimitropoulos A, Scaglione S, Schenone A, Viti F. “A Grid based solution for management and analysis of microarrays in distributed experiments” BMC Bioinform. (accepted).
Romano P, Bertolini G, De Paoli F, Fattore M, Marra D, Mauri G, Merelli E, Porro I, Scaglione S, Milanesi L. “Oncology over Internet: integrating data and analysis of oncology interest on the net by means of workflows”, International Workshop on Integrative Bioinformatics Complex Metabolic Networks, Bielefeld, Germany, July 4–5, 2005.
N. Santos and B. Koblitz, “Metadata services on the grid”, in Proc. of Advanced Computing and Analysis Techniques (ACAT’05), Zeuthen, Berlin, May 2005.
Stratowa C. “XPS, a novel framework for distributed storage and analysis of microarray data in the terabyte range: an alternative to bioConductor”, Proceedings of the 3rd International Workshop on Distributed Statistical Computing, 2003.
Thorsten F. “ODD genes – from microarray data to discovery, using the Grid and high performance computing”, Scottish Center for Genomics Technology and Informatics (SC-GTI) 3rd E-BioSci/ORIEL Annual Workshop, Hinxton Hall Conference Centre, Hinxton, England, October 12–15, 2004, www.gti.ed.ac.uk.
Tuecke S, Welch V, Engert D, Pearlman L, Thompson M. “Internet X.509 public key infrastructure (PKI) proxy certificate profile”, IETF RFC 3820, June 2004.
“Towards Virtual Physiological Human: multilevel modelling and simulation of the human anatomy and physiology – White Paper”, edited by European Commission – DG INFSO & DG JRC, Bruxelles, December 2005.
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Porro, I., Torterolo, L., Fato, M., Schenone, A., Melato, M. (2009). Using the Grid for the Interactive Workflow Management in Biomedicine. In: Davoli, F., Meyer, N., Pugliese, R., Zappatore, S. (eds) Grid Enabled Remote Instrumentation. Signals and Communication Technology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09663-6_39
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DOI: https://doi.org/10.1007/978-0-387-09663-6_39
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