@article{Ellrott2002,
title = {Identifying transcription factor binding sites through markov chain
optimization},
author = {Kyle Ellrott and Chuhu Yang and Frances M. Sladek and Tao Jiang},
journal = {Bioinformatics},
number = {Suppl. 2},
pages = {S100--S109},
url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12385991},
volume = {18},
year = {2002},
abstract = {Even though every cell in an organism contains the same genetic material,
each cell does not express the same cohort of genes. Therefore, one
of the major problems facing genomic research today is to determine
not only which genes are differentially expressed and under what
conditions, but also how the expression of those genes is regulated.
The first step in determining differential gene expression is the
binding of sequence-specific DNA binding proteins (i.e. transcription
factors) to regulatory regions of the genes (i.e. promoters and enhancers).
An important aspect to understanding how a given transcription factor
functions is to know the entire gamut of binding sites and subsequently
potential target genes that the factor may bind/regulate. In this
study, we have developed a computer algorithm to scan genomic databases
for transcription factor binding sites, based on a novel Markov chain
optimization method, and used it to scan the human genome for sites
that bind to hepatocyte nuclear factor 4 alpha (HNF4alpha). A list
of 71 known HNF4alpha binding sites from the literature were used
to train our Markov chain model. By looking at the window of 600
nucleotides around the transcription start site of each confirmed
gene on the human genome, we identified 849 sites with varying binding
potential and experimentally tested 109 of those sites for binding
to HNF4alpha. Our results show that the program was very successful
in identifying 77 new HNF4alpha binding sites with varying binding
affinities (i.e. a 71\% success rate). Therefore, this computational
method for searching genomic databases for potential transcription
factor binding sites is a powerful tool for investigating mechanisms
of differential gene regulation.},
keywords = {Markov TFBS }
}
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