Skip to main content
Article thumbnail
Location of Repository


By E. Wijaya and R. Kanagasabai


In this paper we propose a novel approach for identification of generic motifs in an integrated manner by introducing the notion of submotifs. We formulate the motif finding problem as a constrained submotif pattern mining and present an algorithm called SPACE for identifying motifs that may contain spacers. When spacers are present, we show that the algorithm can identify motifs where 1) the spacers may be of varying lengths, 2) the number of motif segments may be unknown, and 3) the lengths of motif segments may be unknown. We perform rigorous experiments with the Motif Assessment Benchmarks by Tompa et al., and observe that our algorithm overall is able to outperform all popular algorithms tested so far, with significant improvements on sensitivity and specificity. 1

Year: 2009
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.