title: Discussion of "A Bayesian approach to DNA sequence segmentation".
abstract: This article discusses the results in Boys and Henderson (2004, Biometrics 60, 573-581) in which the authors propose a new approach to the classification of genomic DNA into a number of hidden Markov states with a variable order of dependency, potentially allowing for the high-throughput detection of structure within genomic DNA. This article is likely to be an important point of departure for further modeling of this type. We question whether the genome of the bacteriophage lambda is the most appropriate example with which to demonstrate the method's effectiveness, whether it can be expected that the method will carry over to genomes where there is only one direction of transcription and no operon structure, and suggest a graphical display that seems to offer insight into the results. It would be interesting to see an analysis that uses the codon alphabet.
authors: Centre for Bioinformation Science, Australian National University, Australia.
authors: Hilary S
authors: HS
authors: Booth
authors: Conrad J
authors: CJ
authors: Burden
authors: John H
authors: JH
authors: Maindonald
authors: Lucia
authors: L
authors: Santoso
authors: Matthew J
authors: MJ
authors: Wakefield
authors: Susan R
authors: SR
authors: Wilson
mesh_terms: D000465:Algorithms; D010582:Bacteriophage lambda / Q000235:genetics; D001499:Bayes Theorem; D001699:Biometry; D004279:DNA, Viral / Q000235:genetics; D016679:Genome, Viral; D008390:Markov Chains; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D025341:Principal Component Analysis; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data*
chemical_list: D004279:DNA, Viral