• DocumentCode
    2682126
  • Title

    Entropy-based analysis of ChIP-Sequencing data

  • Author

    Zare, Hossein ; Kaveh, Mostafa ; Khodursky, Arkady B.

  • Author_Institution
    Dept. of ECE, Univ. of Minnesota, Minneapolis, MN, USA
  • fYear
    2009
  • fDate
    17-21 May 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    ChIP-Sequencing (ChIP-Seq) is an advanced emerging technology to detect protein-DNA associations and to identify transcription factor binding sites. This technology, which is an alternative to the ChIP-on-chip technique, provides several advantages including data with higher resolution and quality. In this paper we present a framework for the analysis of ChIP-Seq data in order to identify targets of a transcription factor and its binding sites. The introduced method employs the relative entropy measure to identify candidate binding regions with high affinity in the genome and then applies a peak-finding algorithm to locate the local peak(s) within each region. We have applied this method to analyze chromosomal binding patterns of Lrp, a global transcriptional regulator of amino acid metabolism in Escherichia coli.
  • Keywords
    DNA; entropy; genomics; lab-on-a-chip; microorganisms; molecular biophysics; proteins; ChIP-on-chip technique; ChIP-sequencing data; Escherichia coli; amino acid metabolism; chromosomal binding pattern; entropy-based analysis; genome; protein-DNA association detection; transcription factor binding site; Amino acids; Bioinformatics; Biological cells; Data analysis; Entropy; Genomics; Pattern analysis; Proteins; Regulators; Semiconductor device measurement; Chip Sequencing; DNA Binding sites; Relative Entropy; Transcription Factor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genomic Signal Processing and Statistics, 2009. GENSIPS 2009. IEEE International Workshop on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    978-1-4244-4761-9
  • Electronic_ISBN
    978-1-4244-4762-6
  • Type

    conf

  • DOI
    10.1109/GENSIPS.2009.5174339
  • Filename
    5174339