Identification of structured motifs

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
Pages249-253
Number of pages5
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009 - Washington, DC, United States
Duration: Nov 1 2009Nov 4 2009

Other

Other2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
CountryUnited States
CityWashington, DC
Period11/1/0911/4/09

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ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Sheng, H., Mehrotra, K., Mohan, C. K., & Raina, R. (2009). Identification of structured motifs. In Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009 (pp. 249-253). [5332103] https://doi.org/10.1109/BIBMW.2009.5332103