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Application of information-theoretic tests for the analysis of DNA sequences based on Markov chain models

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  • Usotskaya, N.
  • Ryabko, B.

Abstract

The statistical structure of DNA sequences is of great interest to molecular biology, genetics and the theory of evolution. One popular approach is sequence modeling using Markov processes of different orders, and further statistical estimation of their parameters. To continue the investigations according to this approach, tests for hypothesis testing are used to estimate the "memory" (or connectivity) of genetic texts and to solve the DNA-based problem relating to the phylogenetic system of various groups of organisms.

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  • Usotskaya, N. & Ryabko, B., 2009. "Application of information-theoretic tests for the analysis of DNA sequences based on Markov chain models," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1861-1872, March.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:5:p:1861-1872
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    Cited by:

    1. Karatzoglou, Alexandros & Feinerer, Ingo, 2010. "Kernel-based machine learning for fast text mining in R," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 290-297, February.

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