TECHNIQUE FOR THE ANALYSIS OF BIOINFORMATION DATA OF GENOMIC NATURE FOR THE DEVELOPMENT OF MULTIEPITOPE ANTICORONAVIRUS VACCINE MODELS 

Matvey V. Sprindzhuk, Candidate of technical sciences, senior computer scientist, United Institute of Informatics Problems of the Belarus National Academy of Sciences (6 Surganova street, Minsk, Republic of Belarus), E-mail: stepanenkomatvei@yandex.ru
Aleksandr S. Vladyko, Doctor of medical sciences, professor, principal researcher, Republican Scientific and Practical Center for Epidemiology and Microbiology Ministry of Health of the Republic of Belarus (23 Filimonova street, Minsk, Republic of Belarus), E-mail: vladyko@belriem.by
Zhuozhuang Lu, Doctor of medical sciences, professor, principal (head) researcher, Chinese Center for Disease Control and Prevention (155 Changbai Road, Beijing, China), E-mail: luzzbj@aliyun.com
Leonid P. Titov, Doctor of medical sciences, professor, academic of NASB, head of laboratory of experimental immunology, Republican Scientific and Practical Center for Epidemiology and Microbiology Ministry of Health of the Republic of Belarus (23 Filimonova street, Minsk, Republic of Belarus), E-mail: leotit310@gmail.com
Vasiliy I. Bernik, Doctor of physical and mathematical sciences, professor, chief researcher of the department of number theory, Institute of Mathematics of the National Academy of Sciences of Belarus (11 Surganova street, Minsk, Republic of Belarus), Email: bernik@im.bas-net.by 

Background. The coronavirus epidemic continues, but there is evidence that the society has already mastered effective measures for the prevention and treatment of this disease. The unresolved problems are prevention, early diagnosis and timely treatment of new viral epidemics, prevention and treatment of postcovid complications, the mortality from which manifests itself latently under the guise of other diseases and does not fall into the statistics of the coronavirus pandemic. Materials and methods. Based on the developed original data processing technique, designed for analyzing coronavirus genomic data, models of the anti-coronavirus multi-epitope vaccine were computed and tested in silico. In a series of computational experiments, evidence of their possible efficiency and safety was obtained. Results and conclusions. Based on research experiments and analysis of scientific literature, recommendations are formulated for the development and application of epitope antiviral vaccines using the example of the anti-coronavirus vaccine. 

medical systems, information representation, software, algorithms, databases, genomics, transcriptomics, machine learning, artificial intelligence, programming languages, applied mathematics, biophysics, data science, data mining, coronavirus, epidemic, pandemic, bioinformatics, immunoinformatics, antiviral therapy, vaccines, epitopes 

Sprindzuk M.V., Vladyko A.S., Zhuozhuang Lu, Titov L.P., Bernik V.I. Technique for the analysis of bioinformation data of genomic nature for the development of multiepitope anticoronavirus vaccine models. Izmerenie. Monitoring. Upravlenie. Kontrol' = Measuring. Monitoring. Management. Control. 2023;(3):48–58. (In Russ.). doi: 10.21685/2307-5538-2023-3-6