• DocumentCode
    2369833
  • Title

    Identification of structured motifs

  • Author

    Sheng, Huitao ; Mehrotra, Kishan ; Mohan, Chilukuri ; Raina, Ramesh

  • Author_Institution
    Dept. of Electr. Eng.&Comput. Sci., Syracuse Univ., Syracuse, NY, USA
  • fYear
    2009
  • fDate
    1-4 Nov. 2009
  • Firstpage
    249
  • Lastpage
    253
  • Abstract
    Structured motifs consist of two simpler patterns (half-sites) separated from each other by a gap, with no restriction on the nucleotides that may occur within the gap. This paper proposes a new algorithm to identify structured motifs. First, a simpler motif searching algorithm is used to search for half-sites. Candidate structured motif models are then evaluated, based on the relative frequency of occurrence of half-sites (not attributable to randomness), and the distribution of gap length. Unlike other recent structured motif detection algorithms, the new algorithm does not require the gap length to be prespecified.
  • Keywords
    biology computing; cellular biophysics; genetics; gap length; half-sites; motif searching algorithm; nucleotides; structured motifs; Algorithm design and analysis; Biology; Computer science; DNA; Detection algorithms; Frequency; Gene expression; Organisms; Random sequences; Stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-5121-0
  • Type

    conf

  • DOI
    10.1109/BIBMW.2009.5332103
  • Filename
    5332103