Advertisement

Design and Implementation of Computational Bioinformatics Grid Services on GT4 Platforms

  • Chao-Tung Yang
  • Tsu-Fen Han
  • Ya-Ling Chen
  • Heng-Chuan Kan
  • William C. Chu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4494)

Abstract

Availability of computer resources is key factor limiting use of bioinformatics analyses as a result of the growing computational demands. Grid computing provides a way to meet these requirements. But it is complicated to build a grid for users. This paper describes an approach to solve this problem using Grid Service technologies. Building the grid based on accepted standards and platforms makes the development and deployment of the grid much easier. A bioinformatics grid computing environment (BioGrid) which consists of the distributed computing application for bioinformatics is presented in this paper. Based on this environment, we propose the architecture of bioinformatics applications which is delivered using Grid Services constructed with the Globus Toolkit 4. We developed a simple program which is defined as the client-server application with grid services. It provides users an approach of grid services to impose grid resources and customize their own grid applications.

Keywords

Basic Local Alignment Search Tool Master Node Grid Service Grid Application Target Database 
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.
    Alexander, S., Bernhard, M., Roland, P., Johannes, R., Thomas, T., Zlatko, T.: Client-Server Environment for High-Performance Gene Expression Data Analysis. Bioinformatics 19(6), 772–773 (2003)CrossRefGoogle Scholar
  2. 2.
    Bala, P., Jaroslaw, P., Miroslaw, N.: BioGRID – An European Grid for Molecular Biology. In: Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing, p. 412 (2002)Google Scholar
  3. 3.
    Foster, I.: The Grid: A New Infrastructure for 21st Century Science. Physics Today 55(2), 42–47 (2002)CrossRefGoogle Scholar
  4. 4.
    Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure (Elsevier Series in Grid Computing), 2nd edn. Morgan Kaufmann, San Francisco (2004)Google Scholar
  5. 5.
    Foster, I., Kesselman, C.: Globus: A metacomputing infrastructure toolkit. The International Journal of Supercomputer Applications and High. Performance Computing 11(2), 115–128 (1997)CrossRefGoogle Scholar
  6. 6.
    Gernot, S., Dietmar, R., Zlatko, T.: ClusterControl: A Web Interface for Distributing and Monitoring Bioinformatics Applications on a Linux Cluster. Bioinformatics 20, 805–807 (2004)CrossRefGoogle Scholar
  7. 7.
    Fumikazu, K., Tomoyuki, Y., Akinobu, F., Xavier, D., Kenji, S., Akihiko, K.: OBIGrid: A New Computing Platform for Bioinformatics. Genome Informatics 13, 484–485 (2002)Google Scholar
  8. 8.
  9. 9.
    Micha, B., Campbell, A., Virdee, D.: A GT3 based. BLAST grid service for biomedical research. In: Proceedings of the UK e-Science All Hands Meeting (2004)Google Scholar
  10. 10.
  11. 11.
    Oswaldo, T., Miguel, A., Alfonso, V., Zapata, E.L., Carazo, J.M.: Computational Space Reduction and Parallelization of a new Clustering Approach for Large Groups of Sequences. Bioinformatics 14, 439–451 (1998)CrossRefGoogle Scholar
  12. 12.
    Pierce, M., Fox, G., Youn, C., Mock, S., Mueller, K., Balsoy, O.: Interoperable Web services for computational portals. In: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, pp. 1–12 (2002)Google Scholar
  13. 13.
    Suzumura, T., Matsuoka, S., Nakada, H., Casanova, H.: GridSpeed: A Web-based Grid Portal Generation Server. High Performance Computing and Grid in Asia Pacific Region. In: Seventh International Conference on (HPCAsia 2004) pp. 26–33 (2004)Google Scholar
  14. 14.
    Shui, W.M., Wong, R.K.: Application of XML Schema and Active Rules System in Management and Integration of Heterogeneous Biological Data. In: Proceedings of BIBE, pp. 367–374 (2003)Google Scholar
  15. 15.
    Satish, M.K., Joshi, R.R.: GBTK: A Toolkit for Grid Implementation of BLAST. High Performance Computing and Grid in Asia Pacific Region. Seventh International Conference on (HPCAsia 2004) pp. 378–382 (2004)Google Scholar
  16. 16.
    Yang, C.T., Kuo, Y.L., Lai, C.L.: Designing Computing Platform for BioGrid. International Journal of Computer Applications in Technology (IJCAT) 22(1), 3–13 (2005)CrossRefGoogle Scholar
  17. 17.
    Yang, C.T., Kuo, Y.L., Li, K.C., Gaudiot, J.L.: On Design of Cluster and Grid Computing Environments for Bioinformatics Applications. In: Sen, A., Das, N., Das, S.K., Sinha, B.P. (eds.) IWDC 2004. LNCS, vol. 3326, pp. 82–87. Springer, Heidelberg (2004)Google Scholar
  18. 18.
    Yang, C.T., Hsiung, Y.C., Kan, H.C.: Implementation and Evaluation of a Java Based Computational Grid for Bioinformatics Applications. In: Proceedings of the International Conference on Advanced Information Networking and Applications (AINA 2005), vol. 1, pp. 298–303 (2005)Google Scholar
  19. 19.
    Yang, C.T., Kuo, Y.L., Lai, C.L.: Design and Implementation of a Computational Grid for Bioinformatics. In: Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE 2004) pp. 448–451 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Chao-Tung Yang
    • 1
  • Tsu-Fen Han
    • 1
  • Ya-Ling Chen
    • 1
  • Heng-Chuan Kan
    • 2
  • William C. Chu
    • 1
  1. 1.High-Performance Computing Laboratory, Department of Computer Science and Information Engineering, Tunghai University, Taichung City, 40704Taiwan
  2. 2.Southern Business Unit, National Center for High-Performance Computing, Hsinshi, Tainan, 74147Taiwan

Personalised recommendations