• DocumentCode
    3394139
  • Title

    Comparison of feature selection techniques for viral DNA replication origin prediction

  • Author

    Cruz-Cano, Raul ; Leung, Ming-Ying

  • Author_Institution
    Texas A&M Univ.-Texarkana, Texarkana, TX
  • fYear
    2009
  • fDate
    March 30 2009-April 2 2009
  • Firstpage
    128
  • Lastpage
    134
  • Abstract
    As the replication of their DNA genomes is a central step in the reproduction of many viruses, procedures to find replication origins, which are initiation sites of the DNA replication process, are of great importance for controlling the growth and spread of such viruses. Existing computational methods for viral replication origin prediction have mostly been designed to use only the composition of a region of viral DNA to predict if such region is an ORI or not. This paper proposes the application of several feature selection techniques to help find the most significant features of the replication origins in herpesviruses. The results suggest that features based on the relative positions of the regions in the genomes containing replication origins and the information about the subfamily of the virus can be highly useful features to be incorporated into the computational tools for viral replication origin prediction.
  • Keywords
    DNA; biology computing; feature extraction; genomics; microorganisms; molecular biophysics; DNA genomes; feature selection technique; herpes virus; viral DNA replication origin prediction; Accuracy; Artificial neural networks; Bioinformatics; DNA; Genomics; Input variables; Machine learning; Sequences; Support vector machines; Viruses (medical);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09. IEEE Symposium on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    978-1-4244-2756-7
  • Type

    conf

  • DOI
    10.1109/CIBCB.2009.4925718
  • Filename
    4925718