  We propose a solution on the stopping criterion in segmenting inhomogeneous
DNA sequences with complex statistical patterns. This new stopping criterion is
based on Bayesian Information Criterion (BIC) in the model selection framework.
When this stopping criterion is applied to a left telomere sequence of yeast
Saccharomyces cerevisiae and the complete genome sequence of bacterium
Escherichia coli, borders of biologically meaningful units were identified
(e.g. subtelomeric units, replication origin, and replication terminus), and a
more reasonable number of domains was obtained. We also introduce a measure
called segmentation strength which can be used to control the delineation of
large domains. The relationship between the average domain size and the
threshold of segmentation strength is determined for several genome sequences.

Biological Physics;Data Analysis, Statistics and Probability;Genomics