• DocumentCode
    1681499
  • Title

    Supporting high performance bioinformatics flat-file data processing using indices

  • Author

    Zhang, Xuan ; Agrawal, Gagan

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    As an essential part of in vitro analysis, biological database query has become more and more important in the research process. A few challenges that are specific to bioinformatics applications are data heterogeneity, large data volume and exponential data growth, constant appearance of new data types and data formats. We have developed an integration system that processes data in their flat file formats. Its advantages include the reduction of overhead and programming efforts. In the paper, we discuss the usage of indicing techniques on top of this flat file query system. Besides the advantage of processing flat files directly, the system also improves its performance and functionality by using indexes. Experiments based on real life queries are used to test the integration system.
  • Keywords
    biology computing; query processing; biological database query; data heterogeneity; flat file data processing; flat file query system; high performance bioinformatics; indexes; Bioinformatics; Computer science; Data analysis; Data engineering; Data processing; Databases; In vitro; Indexing; Performance analysis; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on
  • Conference_Location
    Miami, FL
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-1693-6
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2008.4536176
  • Filename
    4536176