This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop
Identification of structured motifs
Washington, DC USA
November 01-November 04
ISBN: 978-1-4244-5121-0
Huitao Sheng, Dept. of Electr. Eng.&Comput. Sci., Syracuse Univ., Syracuse, NY, USA
K. Mehrotra, Dept. of Electr. Eng.&Comput. Sci., Syracuse Univ., Syracuse, NY, USA
C. Mohan, Dept. of Electr. Eng.&Comput. Sci., Syracuse Univ., Syracuse, NY, USA
R. Raina, Dept. of Biol., Syracuse Univ., Syracuse, NY, USA
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.
Index Terms:
gap length, structured motifs, nucleotides, motif searching algorithm, half-sites
Citation:
Huitao Sheng, K. Mehrotra, C. Mohan, R. Raina, "Identification of structured motifs," bibmw, pp.249-253, 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop, 2009
Usage of this product signifies your acceptance of the Terms of Use.