Skip to main content
SpringerLink
Log in

Using compositions of Markov models to determine functional gene fragments

  • Published:
Cybernetics and Systems Analysis Aims and scope

Abstract

Algorithmic compositions in the form of expert mixtures with exclusive competence zones are considered in order to increase the quality of classification of gene fragments with the help of models based on Markov chains.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M. Stanke and S. Waack, “Gene prediction with a hidden Markov model and a new intron submodel,” Bioinformatics, 19, Suppl. 2, 215–225 (2003).

    Google Scholar 

  2. W. H. Majoros, M. Pertea, and S. L. Salzberg, “TigrScan and GlimmerHMM: Two open source ab initio eukaryotic gene-finders,” Bioinformatics, 20, No. 16, 2878–2879 (2004).

    Article  Google Scholar 

  3. I. V. Sergienko, A. M. Gupal, and A. V. Ostrovsky, “Recognition of DNA gene fragments using hidden Markov models,” Cybern. Syst. Analysis, 48, No. 3, 369–377 (2012).

    Article  Google Scholar 

  4. K. Knapp and Y.-P. P. Chen, “An evaluation of contemporary hidden Markov model genefinders with a predicted exon taxonomy,” Nucleic Acids Research, 35, 317–324 (2007).

    Article  Google Scholar 

  5. A. T. Sumner, J. de la Torre, and L. Stuppia, “The distribution of genes on chromosomes: A cytological approach,” J. Mol. Evol., 37, No. 2, 117–122 (1993).

    Article  Google Scholar 

  6. B. Aïssani and G. Bernardi, “CpG islands, genes and isochores in the genomes of vertebrates,” Gene, 106, No. 2, 185–195 (1991).

    Article  Google Scholar 

  7. I. V. Sergienko, B. A. Beletskii, S. V. Vasil’ev, and A. M. Gupal, “Predicting protein secondary structure based on Bayesian classification procedures on Markov chains,” Cybern. Syst. Analysis, 43, No. 2, 208–212 (2007).

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

    A. M. Gupal

  2. Kyiv Branch of the Moscow Institute of Physics and Technology, PhTSTC of the National Academy of Sciences of Ukraine, Kyiv, Ukraine

    A. V. Ostrovsky

Authors
  1. A. M. Gupal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. V. Ostrovsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. M. Gupal.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 5, September–October, 2013, pp. 61–68.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gupal, A.M., Ostrovsky, A.V. Using compositions of Markov models to determine functional gene fragments. Cybern Syst Anal 49, 692–698 (2013). https://doi.org/10.1007/s10559-013-9556-6

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10559-013-9556-6

Keywords

Search

Navigation