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A hidden Markov model for analyzing ChIP-chip experiments on genome tiling arrays and its application to p53 binding sequences
Author(s) -
Wei Li,
Clifford A. Meyer,
X. S. Liu
Publication year - 2005
Publication title -
computer applications in the biosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1460-2059
pISSN - 0266-7061
DOI - 10.1093/bioinformatics/bti1046
Subject(s) - tiling array , chromatin immunoprecipitation , genome , hidden markov model , computational biology , dna microarray , dna binding site , biology , gene , genetics , computer science , gene expression , promoter , artificial intelligence
Transcription factors (TFs) regulate gene expression by recognizing and binding to specific regulatory regions on the genome, which in higher eukaryotes can occur far away from the regulated genes. Recently, Affymetrix developed the high-density oligonucleotide arrays that tile all the non-repetitive sequences of the human genome at 35 bp resolution. This new array platform allows for the unbiased mapping of in vivo TF binding sequences (TFBSs) using Chromatin ImmunoPrecipitation followed by microarray experiments (ChIP-chip). The massive dataset generated from these experiments pose great challenges for data analysis.

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