Abstract
Recently, we proposed a new measure of complexity for symbolic sequences (Sequence Compositional Complexity, SCC) based on the entropic segmentation of a sequence into compositionally homogeneous domains. Such segmentation is carried out by means of a conceptually simple, computationally efficient heuristic algorithm. SCC is now applied to the sequences generated by several stochastic models which describe the statistical properties of DNA, in particular the observed long-range fractal correlations. This approach allows us to test the capability of the different models in describing the complex compositional heterogeneity found in DNA sequences. Moreover, SCC detects clear differences where conventional standard methods fail.
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