Advertisement

Data Access and Integration in the ISPIDER Proteomics Grid

  • Lucas Zamboulis
  • Hao Fan
  • Khalid Belhajjame
  • Jennifer Siepen
  • Andrew Jones
  • Nigel Martin
  • Alexandra Poulovassilis
  • Simon Hubbard
  • Suzanne M. Embury
  • Norman W. Paton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4075)

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.

Keywords

Data Integration Global Schema Transformation Pathway Data Integration System Query Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alpdemir, M.N., Mukherjee, A., Paton, N.W., Watson, P., Fernandes, A.A., Gounaris, A., Smith, J.: Service-based distributed querying on the Grid. In: Proc. of the 1st Int. Conf. on Service Oriented Computing, pp. 467–482 (2003)Google Scholar
  2. 2.
    Antonioletti, M., et al.: The design and implementation of grid database services in OGSA-DAI. Concurrency - Practice and Experience 17(2-4), 357–376 (2005)CrossRefGoogle Scholar
  3. 3.
    Bowers, S., Ludäscher, B.: An ontology-driven framework for data transformation in scientific workflows. In: Rahm, E. (ed.) DILS 2004. LNCS (LNBI), vol. 2994, pp. 1–16. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Buneman, P., Libkin, L., Suciu, D., Tannen, V., Wong, L.: Comprehension syntax. SIGMOD Record 23(1), 87–96 (1994)CrossRefGoogle Scholar
  5. 5.
    Cattell, R.G.G., Barry, D.K.: The Object Database Standard: ODMG 3.0. Morgan Kaufmann, San Francisco (2000)Google Scholar
  6. 6.
    Craig, R., Cortens, J.P., Beavis, R.C.: Open source system for analyzing, validating, and storing protein identification data. Journal of Proteome Research 3(6) (2004)Google Scholar
  7. 7.
    Davidson, S.B., Overton, C., Tannen, V., Wong, L.: BioKleisli: A Digital Library for Biomedical Researchers. Journal of Digital Libraries 1(1), 36–53 (1997)Google Scholar
  8. 8.
    Durinck, S., Moreau, Y., Kasprzyk, A., Davis, S., De Moor, B., Brazma, A., Huber, W.: Biomart and bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics 21(16), 3439–3440 (2005)CrossRefGoogle Scholar
  9. 9.
    Garwood, K., et al.: Pedro: A database for storing, searching and disseminating experimental proteomics data. BMC Genomics 5 (2004)Google Scholar
  10. 10.
    Goble, C.A., Stevens, R., Ng, G., Bechhofer, S., Paton, N.W., Baker, P.G., Peim, M., Brass, A.: Transparent access to multiple bioinformatics information sources. IBM Systems Journal 40(2), 532–551 (2001)CrossRefGoogle Scholar
  11. 11.
    Haas, L.M., Schwarz, P.M., Kodali, P., Kotlar, E., Rice, J.E., Swope, W.C.: Discoverylink: A system for integrated access to life sciences data sources. IBM Systems Journal 40(2), 489–511 (2001)CrossRefGoogle Scholar
  12. 12.
    Jasper, E., Poulovassilis, A., Zamboulis, L.: Processing IQL queries and migrating data in the AutoMed toolkit. AutoMed Tech. Rep. 20 (June 2003)Google Scholar
  13. 13.
    Maibaum, M., Zamboulis, L., Rimon, G., Orengo, C., Martin, N., Poulovassilis, A.: Cluster Based Integration of Heterogeneous Biological Databases Using the AutoMed Toolkit. In: Ludäscher, B., Raschid, L. (eds.) DILS 2005. LNCS (LNBI), vol. 3615, pp. 191–207. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  14. 14.
    Mçbrien, P., Poulovassilis, A.: Defining Peer-to-Peer Data Integration Using Both as View Rules. In: Aberer, K., Koubarakis, M., Kalogeraki, V. (eds.) VLDB 2003. LNCS, vol. 2944, pp. 91–107. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    McBrien, P., Poulovassilis, A.: Data integration by bi-directional schema transformation rules. In: Proc. ICDE 2003, pp. 227–238 (2003)Google Scholar
  16. 16.
    McLaughlin, T., Siepen, J.A., Selley, J., Lynch, J.A., Lau, K.W., Yin, H., Gaskell, S.J., Hubbard, S.J.: Pepseeker: a database of proteome peptide identifications for investigating fragmentation patterns. Nucleic Acids Research 34 (2006)Google Scholar
  17. 17.
    Oinn, T.M., Addis, M., Ferris, J., Marvin, D., Senger, M., Greenwood, R.M., Carver, T., Glover, K., Pocock, M.R., Wipat, A., Li, P.: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20(17), 3045–3054 (2004)CrossRefGoogle Scholar
  18. 18.
    Perkins, D.N., Pappin, D.J., Creasy, D.M., Cottrell, J.S.: Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20(18) (1999)Google Scholar
  19. 19.
    Pruess, M., Kersey, P., Apweiler, R.: The integr8 project - a resource for genomic and proteomic data. In: Silico Biology, vol. 5 (2004)Google Scholar
  20. 20.
    Shah, S.P., Huang, Y., Xu, Y., Yuen, M.M.S., Ling, J., Ouellette, B.F.F.: Atlas – a data warehouse for integrative bioinformatics. BMC Bioinformatics 6(81) (2005)Google Scholar
  21. 21.
    Smith, J., Gounaris, A., Watson, P., Paton, N.W., Fernandes, A.A.A., Sakellariou, R.: Distributed query processing on the grid. In: Parashar, M. (ed.) GRID 2002. LNCS, vol. 2536, pp. 279–290. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  22. 22.
    Zdobnov, E.M., Lopez, R., Apweiler, R., Etzold, T.: The EBI SRS server-recent developments. Bioinformatics 18(2), 368–373 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lucas Zamboulis
    • 1
    • 2
  • Hao Fan
    • 1
    • 2
  • Khalid Belhajjame
    • 3
  • Jennifer Siepen
    • 3
  • Andrew Jones
    • 3
  • Nigel Martin
    • 1
  • Alexandra Poulovassilis
    • 1
  • Simon Hubbard
    • 3
  • Suzanne M. Embury
    • 4
  • Norman W. Paton
    • 4
  1. 1.School of Computer Science and Information SystemsUniv. of LondonBirkbeck
  2. 2.Department of Biochemistry and Molecular BiologyUniversity College London 
  3. 3.Faculty of Life SciencesUniversity of Manchester 
  4. 4.School of Computer ScienceUniversity of Manchester 

Personalised recommendations