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Identification of Transcription Factor Binding Sites in Promoter Regions by Modularity Analysis of the Motif Co-occurrence Graph

  • Alexandre P. Francisco
  • Arlindo L. Oliveira
  • Ana T. Freitas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4983)

Abstract

Many algorithms have been proposed to date for the problem of finding biologically significant motifs in promoter regions. They can be classified into two large families: combinatorial methods and probabilistic methods. Probabilistic methods have been used more extensively, since their output is easier to interpret. Combinatorial methods have the potential to identify hard to detect motifs, but their output is much harder to interpret, since it may consist of hundreds or thousands of motifs. In this work, we propose a method that processes the output of combinatorial motif finders in order to find groups of motifs that represent variations of the same motif, thus reducing the output to a manageable size. This processing is done by building a graph that represents the co-occurrences of motifs, and finding communities in this graph. We show that this innovative approach leads to a method that is as easy to use as a probabilistic motif finder, and as sensitive to low quorum motifs as a combinatorial motif finder. The method was integrated with two combinatorial motif finders, and made available on the Web.

Keywords

Transcription Factor Binding Site Combinatorial Method Complex Motif Sparse Graph Relation Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alexandre P. Francisco
    • 1
  • Arlindo L. Oliveira
    • 1
  • Ana T. Freitas
    • 1
  1. 1.INESC-ID/ISTTechnical University of LisbonPortugal

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