Abstract
For every disease, there is a certain set of genes whose mutations increase the risk of illness development. DNA sequencing of sick and healthy individuals results in the determination of genes related to certain diseases. Efficient procedures are described in order to determine point mutations in gene sequences of the examined patients. The optimal Bayesian procedure is used to determine risk groups for certain diseases, including the ones that underlie COVID-19.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
I. V. Sergienko, A. M. Gupal, and A. V. Ostrovskii, “Noise immunity of genetic codes to point mutations,” Cybern. Syst. Analysis, Vol. 50, No. 5, 663–669 (2014). https://doi.org/10.1007/s10559-014-9656-y.
I. V. Sergienko, B. A. Biletskyy, A. M. Gupal, and M. A. Gupal, “Optimal noise-immune genetic codes,” Cybern. Syst. Analysis, Vol. 55, No. 1, 34–39 (2019). https://doi.org/10.1007/s10559-019-00110-1.
T. A. Brown, Genomes 3, Garland Sci. (2006).
A. M. Gupal, S. V. Pashko, and I. V. Sergienko, “Efficiency of Bayesian classification procedure,” Cybern. Syst. Analysis, Vol. 31, No. 4, 543–554 (1995). https://doi.org/10.1007/BF02366409.
I. V. Sergienko, A. M. Gupal, and S. V. Pashko, “Complexity of classification problems,” Cybern. Syst. Analysis, Vol. 32, No. 4, 519–533 (1996). https://doi.org/10.1007/BF02366774.
I. V. Sergienko, A. M. Gupal, and A. V. Ostrovsky, “Recognition of DNA gene fragments using hidden Markov models,” Cybern. Syst. Analysis, Vol. 48, No. 3, 369–377 (2012). https://doi.org/10.1007/s10559-012-9416-9.
A. M. Gupal and A. V. Ostrovsky, “Using compositions of Markov models to determine functional gene fragments,” Cybern. Syst. Analysis, Vol. 49, No. 5, 692–698 (2013). https://doi.org/10.1007/s10559-013-9556-6.
A. M. Gupal, M. A. Gupal, and A. L. Tarasov, “Bayesian procedures of hematologic disease recognition,” Cybern. Syst. Analysis, Vol. 53, No. 6, 925–930 (2017). https://doi.org/10.1007/s10559-017-9994-7.
N. Ya. Gridina, A. M. Gupal, A. L. Tarasov, and Yu. V. Ushenin, “Analysis of neurosurgical pathologies using Bayesian recognition procedures for indicators of surface plasmon resonance in the aggregation of blood cells,” Cybern. Syst. Analysis, Vol. 56, No. 4, 550–558 (2020). https://doi.org/10.1007/s10559-020-00271-4.
Author information
Authors and Affiliations
Corresponding author
Additional information
Translated from Kibernetyka ta Systemnyi Analiz, No. 2, March–April, 2021, pp. 62–68.
Rights and permissions
About this article
Cite this article
Vagis, A.A., Gupal, A.M. & Sergienko, I.V. Determination of Risk Groups for the Covid-19 Underlying Deseases. Cybern Syst Anal 57, 223–227 (2021). https://doi.org/10.1007/s10559-021-00347-9
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10559-021-00347-9