title: Finding cis-regulatory modules in Drosophila using phylogenetic hidden Markov models.
abstract: BACKGROUND
  Finding the regulatory modules for transcription factors binding is an important step in elucidating the complex molecular mechanisms underlying regulation of gene expression. There are numerous methods available for solving this problem, however, very few of them take advantage of the increasing availability of comparative genomic data.
  
  
  RESULTS
  We develop a method for finding regulatory modules in Eukaryotic species using phylogenetic data. Using computer simulations and analysis of real data, we show that the use of phylogenetic hidden Markov model can lead to an increase in accuracy of prediction over methods that do not take advantage of the data from multiple species.
  
  
  BACKGROUND
  The new method is made accessible under GPL in a new publicly available JAVA program: EvoPromoter. It can be downloaded at http://sourceforge.net/projects/evopromoter/.
authors.affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. sww8@cornell.edu
authors.forename: Wendy S W
authors.initials: WS
authors.lastname: Wong
authors.forename: Rasmus
authors.initials: R
authors.lastname: Nielsen
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D004330:Drosophila / Q000235:genetics*; D008390:Markov Chains; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D010802:Phylogeny; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*