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Motif Location Prediction by Divide and Conquer

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Bioinformatics Research and Development (BIRD 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 13))

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Abstract

Motif discovery recently received considerable interest from both computational biologists and computer scientists. Identifying motifs is greatly significant for understanding the mechanism behind regulating gene expressions. Although many algorithms have been proposed to solve this problem, only some of them use prior information about motifs. In this paper, we propose a method to limit the search space of the existing methods for motif discovery. Our method is based on the following observation: if some elements are conserved, then these elements may be part of a conserved motif. Further, the proposed approach is based on the divide and conquer concept, where we divide each DNA sequence into four subsequences, one subsequence per each of the four letters, representatives of the nucleotides, namely {A, C, G, T}. Then, we consider the subsequences for G as the major source for deciding on candidate motifs because G is found in almost all the transcription factors binding sites; the decision is supported and enhanced by the subsequences of the other three letters. We have applied this idea to yst04 and hm03r datasets; the results are encouraging as we have successfully predicted the locations of some of the motifs hidden within the analyzed sequences.

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Authors and Affiliations

  1. Department of Computer science, University of Calgary, Calgary, Alberta, Canada

    Mohammed Alshalalfa & Reda Alhajj

Authors
  1. Mohammed Alshalalfa
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  2. Reda Alhajj
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Editor information

Mourad Elloumi Josef Küng Michal Linial Robert F. Murphy Kristan Schneider Cristian Toma

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Alshalalfa, M., Alhajj, R. (2008). Motif Location Prediction by Divide and Conquer. In: Elloumi, M., Küng, J., Linial, M., Murphy, R.F., Schneider, K., Toma, C. (eds) Bioinformatics Research and Development. BIRD 2008. Communications in Computer and Information Science, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70600-7_8

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  • DOI: https://doi.org/10.1007/978-3-540-70600-7_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70598-7

  • Online ISBN: 978-3-540-70600-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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