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Symmetry in DNA: Methods of Pattern Recognition Based on Hidden Markov Models

In: Optimization Methods and Applications

Author

Listed:
  • Borys O. Biletskyy

    (V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine)

  • Anatoliy M. Gupal

    (V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine)

Abstract

Fundamental relations and symmetry rules of the genetic information organization in DNA were studied. DNA symmetry was used to construct an optimal symmetric code with respect to amino acid polarity, with noise immunity much higher than that of a standard genetic code. It is well known that various diseases are associated with pointwise mutations of nucleotides in genes. Bayesian procedures allow for use of the standard and symmetric codes for genetic diseases diagnosis. Markov model of higher orders with hidden states was used to build simple algorithms for gene fragment prediction.

Suggested Citation

  • Borys O. Biletskyy & Anatoliy M. Gupal, 2017. "Symmetry in DNA: Methods of Pattern Recognition Based on Hidden Markov Models," Springer Optimization and Its Applications, in: Sergiy Butenko & Panos M. Pardalos & Volodymyr Shylo (ed.), Optimization Methods and Applications, pages 11-32, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-68640-0_2
    DOI: 10.1007/978-3-319-68640-0_2
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