Advertisement

Malaysian Parasite Database Infrastructure

  • Sarinder K. Dhillon
  • Nur-Imtiazah Shuhaimi
  • Susan Lim Lee Hong
  • Amandeep S. Sidhu
Part of the Studies in Computational Intelligence book series (SCI, volume 477)

Abstract

The Malaysian Parasite Database is set up to collect, digitize, collate, integrate and analyse available literatures on Malaysian parasites to be shared and disseminated through an integrated database system for the generation of knowledge. We adopted the data warehouse approach which is convenient and meets the purpose for the Malaysian Parasite Database. The data includes information on parasite specimens collected besides their taxonomy, biology, ecology, hosts and DNA which will be regularly updated. These data ,which will be regularly updated are initially obtained from literatures and researchers collections which are then digitized and added into the database. We plan to integrate this database with other parasite host databases in order to provide a detailed and comprehensive information on indigenous parasites. This database is envisaged to be dynamic with regular incorporation of new analytical methods and novel use. In this paper, we present the infrastructure of the Malaysian Parasite Database and using a data warehouse approach which uses wrappers for a structured data extraction from related public databases and a structured vocabulary for data integration. The current and future implementations of the proposed infrastructure will be hosted on a cloud environment.

Keywords

Database Data Integration Parasite Data Warehouse Ontology 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Koonin, E.V., Galperin, M.Y.: Prokaryotic genomes: the emerging paradigm of genome-based microbiology. Current Opinions in Genetic Development 7, 757–763 (1997)CrossRefGoogle Scholar
  2. 2.
    Sarinder, K.K.S., Majid, M.A., Lim, L.H.S., Ibrahim, H., Merican, A.F.: Integrated Biological Database Initiative (IBDI). In: Proceedings of International Conference on Biogeography and Biodiversity Wallace in Sarawak – 150 Years Later, Kuching, Malaysia (2005)Google Scholar
  3. 3.
    Merican, A.F., Othman, R., Ismail, N., Cheah, K.P., Mok, L., Yin, Y.K.C., Kaur, S.: Development of Malaysian Indigenous Microorganisms Online Database System. Asia Pacific Journal of Molecular Biology and Biotechnology 10(1), 69–72Google Scholar
  4. 4.
    Guan, S.L., Kirton, L.G.: Biological Collections at the Forest Research Institute Malaysia. In: 22nd Pacific Science Congress, Kuala Lumpur (2011)Google Scholar
  5. 5.
    Napis, S., Salleh, K.M., Itam, K., Latiff, A.: Biodiversity Databases for Malaysian Flora and Fauna: An Update. In: Proceedings of Internet Workshop, National Institute of Informatics, Tokyo, Japan and High Quality Internet Study Group of Information Processing Society of Japan, IPSJ (2001)Google Scholar
  6. 6.
    Kamruzzaman, A.Z.M., Selamat, H., Wahid, M.T.: Conceptual Design of Biodiversity Data Model (BiDaM) using Object Relational and Event Based Approach. In: Proceedings of the Postgraduate Annual Research Seminar 2005, pp. 77–81 (2005)Google Scholar
  7. 7.
    Sprague, J., Bayraktaroglu, L., Clements, D., Conlin, T., Fashena, D., Frazer, K., Haendel, M., Howe, D.G., Mani, P., Ramachandran, S., et al.: The Zebrafish Information Network: the zebrafish model organism database about project success: an exploratory study. Nucleic Acids Research 34, 581–585 (2006)CrossRefGoogle Scholar
  8. 8.
    Zouberakis, M., Chandras, C., Swertz, M., Smedley, D., Gruenberger, M., Bard, J., Schughart, K., Rosenthal, N., Hancock, J.M., Schofield, P.N., Kollias, G., Aidinis, V.: Database, vol. 2010 (2010)Google Scholar
  9. 9.
    Murthy, U., Fox, E.A., Chen, Y., Hallerman, E., da Silva Torres, R., Ramos, E.J., Falcão, T.R.C.: Superimposed Image Description and Retrieval for Fish Species Identification. In: Agosti, M., Borbinha, J., Kapidakis, S., Papatheodorou, C., Tsakonas, G. (eds.) ECDL 2009. LNCS, vol. 5714, pp. 285–296. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Kozievitch, N.P., da Silva Torres, R., Andrade, F., Murthy, U., Fox, E., Hallerman, E.: A teaching tool for parasitology: Enhancing learning with annotation and image retrieval. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds.) ECDL 2010. LNCS, vol. 6273, pp. 466–469. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Lim, L.H.S.: Diversity of monogeneans in Southeast Asia. International Journal for Parasitology 28(10), 1495–1515 (1998)CrossRefGoogle Scholar
  12. 12.
    Lim, L.H.S.: Parasites as indicators of present and past ecology of the environment. In: Tuen, A.A., Das, I. (eds.) Proceedings of the Wallace in Sarawak - 150 Years Later. An International Conference on Biogeography and Biodiversity, pp. 223–224 (2005)Google Scholar
  13. 13.
    Tisdall, J.D.: Mastering Perl for bioinformatics. O’Reilly, Sebastopol (2003)Google Scholar
  14. 14.
    Williams, N.: Bioinformatics: How to Get Databases Talking the Same Language. Science 275, 301–302 (1997)CrossRefGoogle Scholar
  15. 15.
    Etzold, T., Argos, P.: SRS: An Indexing and Retrieval Tool for Flat File Data Libraries. Computer Application of Biosciences 9, 49–57 (1993)Google Scholar
  16. 16.
    Rebhan, M., Chalifa-Caspi, V., Prilusky, J., Lancet, D.: GeneCards: encyclopedia for Genes, Proteins, and Diseases. Weizmann Institute of Science, Bioinformatics Unit and Genome Center, Rehovot, Israel (1997)Google Scholar
  17. 17.
    Fujibuchi, W., Goto, S., Migimatsu, H., Uchiyama, I., Ogiwara, A., Akiyama, Y., Kanehisa, M.: DBGET/LinkDB: an Integrated Database Retrieval System. In: Pacific Symposium of Biocomputing. PSB Electronic Proceedings, Hawaii (1998)Google Scholar
  18. 18.
    Haas, L., Schwarz, P., Kodali, P., Kotlar, E., Rice, J., Swope, W.: DiscoveryLink: A system for integrated access to life sciences data sources. IBM Systems Journal 40, 489–511 (2001)CrossRefGoogle Scholar
  19. 19.
    Davidson, S., Crabtree, J., Brunk, B., Schug, J., Tannen, V., Overton, C., Stoeckert, C.: K2/Kleisli and GUS: Experiments in Integrated Access to Genomic Data Sources. IBM Systems Journal 40, 512–531 (2001)CrossRefGoogle Scholar
  20. 20.
    Buneman, P., Davidson, S., Hart, K., Overton, C., Wong, L.: A Data Transformation System for Biological Data Sources. In: 21st International Conference on Very Large Data Bases (VLDB 1995). Morgan Kaufmann, Zurich (1995)Google Scholar
  21. 21.
    Lu, W., Jackson, J., Ekanayake, J., Barga, R.S., Araujo, N.: Performing Large Science Experiments on Azure: Pitfalls and Solutions. In: Proc. CloudCom, pp. 209–217 (2010)Google Scholar
  22. 22.
    Karp, P.D.: A strategy for database interoperation. Journal of Computational Biology 2, 573–583 (1996)CrossRefGoogle Scholar
  23. 23.
    Ritter, O.: The integrated genomic database. In: Suhai, S. (ed.) Computational Methods in Genome Research. Plenum, New York (1994)Google Scholar
  24. 24.
    Ben-natan, R.: CORBA. McGraw Hill, New York (1995)Google Scholar
  25. 25.
    Achard, F., Barillot, E.: Ubiquitous distributed objects with CORBA. In: Pacific Symposium on Biocomputing, pp. 39–50 (1997)Google Scholar
  26. 26.
    Stein, L.D., Cartinhour, S., Thierry-mieg, D., Thierry-mieg, J.: JADE: An approach for interconnecting bioinformatics databases. Gene 209, 39–43 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sarinder K. Dhillon
    • 1
  • Nur-Imtiazah Shuhaimi
    • 1
  • Susan Lim Lee Hong
    • 1
  • Amandeep S. Sidhu
    • 2
  1. 1.Institute of Biological Sciences, Faculty of ScienceUniversity of MalayaKuala LumpurMalaysia
  2. 2.Curtin Sarawak Research InstituteCurtin UniversitySarawakMalaysia

Personalised recommendations