• DocumentCode
    2192802
  • Title

    Parametric Templates: A New Enzyme Active-Site Prediction Algorithm

  • Author

    Kato, Tsuyoshi ; Suwa, Kazuhiro ; Nagano, Nozomi

  • Author_Institution
    Grad. Sch. of Eng., Gunma Univ., Kiryu, Japan
  • fYear
    2010
  • fDate
    13-13 Dec. 2010
  • Firstpage
    711
  • Lastpage
    718
  • Abstract
    It is an important problem to find functionally analogous enzymes based on the local structures of active-sites. Conventional methods predict active-sites by computing the deviations from the local-structure templates with no statistical parameters. We present a new statistical algorithm that uses parametric templates to compute the deviations of local sites. The parameters of the templates are determined automatically from a set of known active-sites. In this work, promising experimental results are shown through comparison of parametric templates with conventional templates.
  • Keywords
    biology computing; enzymes; proteins; statistical analysis; enzyme active site prediction algorithm; local sites; parametric templates; statistical algorithm; RLCP classification; active-site prediction; machine learning; parametric template; structural analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4244-9244-2
  • Electronic_ISBN
    978-0-7695-4257-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2010.176
  • Filename
    5693366