• DocumentCode
    3600781
  • Title

    CMStalker: A Combinatorial Tool for Composite Motif Discovery

  • Author

    Leoncini, Mauro ; Montangero, Manuela ; Pellegrini, Marco ; Tillan, Karina Panucia

  • Author_Institution
    Dept. of Phys., Univ. of Modena & Reggio Emilia, Modena, Italy
  • Volume
    12
  • Issue
    5
  • fYear
    2015
  • Firstpage
    1123
  • Lastpage
    1136
  • Abstract
    Controlling the differential expression of many thousands different genes at any given time is a fundamental task of metazoan organisms and this complex orchestration is controlled by the so-called regulatory-genome encoding complex regulatory networks: several Transcription Factors bind to precise DNA regions, so to perform in a cooperative manner a specific regulation task for nearby genes. The in silico prediction of these binding sites is still an open problem, notwithstanding continuous progress and activity in the last two decades. In this paper, we describe a new efficient combinatorial approach to the problem of detecting sets of cooperating binding sites in promoter sequences, given in input a database of Transcription Factor Binding Sites encoded as Position Weight Matrices. We present CMStalker, a software tool for composite motif discovery which embodies a new approach that combines a constraint satisfaction formulation with a parameter relaxation technique to explore efficiently the space of possible solutions. Extensive experiments with 12 data sets and 11 state-of-the-art tools are reported, showing an average value of the correlation coefficient of 0.54 (against a value 0.41 of the closest competitor). This improvements in output quality due to CMStalker is statistically significant.
  • Keywords
    DNA; bioinformatics; genomics; CMStalker; DNA region; combinatorial tool; composite motif discovery; metazoan organism; parameter relaxation technique; position weight matrix; promoter sequence; regulatory-genome encoding complex regulatory network; transcription factor binding site database; Bioinformatics; Correlation; Customer relationship management; DNA; Hidden Markov models; Pulse width modulation; Space exploration; Algorithms; Biology and genetics; biology and genetics;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2014.2359444
  • Filename
    6948260