Applications of hidden Markov models for characterization of homologous DNA sequences with a common gene.
Identifying and characterizing the structure in genome sequences is one of the principal challenges in modern molecular biology, and comparative genomics offers a powerful tool. In this paper, we introduce a hidden Markov model that allows a comparative analysis of multiple sequences related by a phylogenetic tree, and we present an efficient method for estimating the parameters of the model. The model integrates structure prediction methods for one sequence, statistical multiple alignment methods, and phylogenetic information. This unified model is particularly useful for a detailed characterization of DNA sequences with a common gene. We illustrate the model on a variety of homologous sequences.
Hobolth
Asger
A
Bioinformatics Research Center, University of Aarhus, Aarhus, Denmark. asger@birc.au.dk
Jensen
Jens Ledet
JL
D016960:Agrobacterium tumefaciens / Q000235:genetics; D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D008390:Markov Chains; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000706:statistics & numerical data*; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data*; D012689:Sequence Homology, Nucleic Acid; D016962:Sinorhizobium meliloti / Q000235:genetics