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
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;
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
DOI :
10.1109/GENSIPS.2009.5174339