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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN On-line: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v43.i11.10
pages 1-7

Bayesian Recognition Procedure of Gene Fragments in DNA

Ivan I. Andreychuk
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev, Ukraine
Anatoliy M. Gupal
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev, Ukraine
Vladimir V. Ryazanov
Dorodnicyn Computing Centre of Russian Academy of Sciences, Moscow

RESUMO

On the basis of instrument of Bayesian approach and Markov chain, the recognition procedure for gene fragments is obtained. The procedure has high percentage of recognition 80−90 % and is simple and effective in computation. The applicability of the 1st order Markov chain to the recognition of gene fragments of genome of an organism Caenorhabditis Elegans is described.

Referências

  1. Gupal A.M., Sergienko I.V., Optimal recognition procedures.

  2. Gupal A.M., Gupal N.A., Ostrovskiy A.V., Symmetry and properties of genetic information recording in DNA.

  3. Sergienko I.V., Gupal A.M., Vagis A.A., Symmetry in encoding genetic information in DNA.

  4. Sergienko I.V., Gupal A.M., Vagis A.A., Symmetry and properties of genetic information record in DNA.

  5. Batzoglou S., Alexandersson M., Pachter L.,Saxonov S. , Gene recognition.

  6. Sergienko I.V., Biletskyy B.A., Gupal A.M., Predicting torsion angles in amino acid protein sequences based on a Bayesian classification procedure on Markov chains.

  7. Palagin A.V., Gupal A.M., Rzhepetskiy S.S., Bayesian recognition procedures of literary texts.

  8. Anderson T.W., Goodman L.A., Statistical inference about Markov chains.


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