title: DNA segmentation through the Bayesian approach.
abstract: We present a new approach to DNA segmentation into compositionally homogeneous blocks. The Bayesian estimator, which is applicable for both short and long segments, is used to obtain the measure of homogeneity. An exact optimal segmentation is found via the dynamic programming technique. After completion of the segmentation procedure, the sequence composition on different scales can be analyzed with filtration of boundaries via the partition function approach.
authors.affiliation: Engelhardt Institute of Molecular Biology, Vavilova, Russia. ramensky@imb.ac.ru
authors.forename: V E
authors.initials: VE
authors.lastname: Ramensky
authors.lastname: Makeev VJu
authors.forename: M A
authors.initials: MA
authors.lastname: Roytberg
authors.forename: V G
authors.initials: VG
authors.lastname: Tumanyan
mesh_terms: D000465:Algorithms; D001482:Base Composition; D001483:Base Sequence; D001499:Bayes Theorem; D001699:Biometry; D004247:DNA / Q000235:genetics*; D004269:DNA, Bacterial / Q000235:genetics; D004271:DNA, Fungal / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics; D016680:Genome, Bacterial; D016681:Genome, Fungal; D015894:Genome, Human; D006801:Humans; D016013:Likelihood Functions; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated; D011336:Probability; D012441:Saccharomyces cerevisiae / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data*
chemical_list: D004269:DNA, Bacterial; D004271:DNA, Fungal; D004247:DNA