Details
| Title | Mathematical modeling in virology and its application to explaining the mechanism of emergence of new SARS-CoV-2 strains: выпускная квалификационная работа магистра: направление 12.04.04 «Биотехнические системы и технологии» ; образовательная программа 12.04.04_01 «Молекулярные и клеточные биомедицинские технологии (международная образовательная программа) / Molecular and Cellular Biomedical Technologies (International Educational Program)» |
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| Creators | Лихачев Игорь Владимирович |
| Scientific adviser | Скворцов Алексей Николаевич |
| Organization | Санкт-Петербургский политехнический университет Петра Великого. Институт биомедицинских систем и биотехнологий |
| Imprint | Санкт-Петербург, 2026 |
| Collection | Выпускные квалификационные работы ; Общая коллекция |
| Subjects | epistasis ; epistasis detection ; genetic linkage ; selection coefficient ; respiratory virus ; virus evolution ; mathematical model ; SARS-CoV-2 |
| Document type | Master graduation qualification work |
| Language | Russian |
| Level of education | Master |
| Speciality code (FGOS) | 12.04.04 |
| Speciality group (FGOS) | 120000 - Фотоника, приборостроение, оптические и биотехнические системы и технологии |
| DOI | 10.18720/SPBPU/3/2026/vr/vr26-4700 |
| Rights | Доступ по паролю из сети Интернет (чтение) |
| Additionally | New arrival |
| Record key | ru\spstu\vkr\45226 |
| Record create date | 9/7/2026 |
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| Group | Anonymous |
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| Network | Internet |
This study examines the application of mathematical modeling methods to explain the emergence of new SARS-CoV-2 strains. Population genetic models were adapted to simulate SARS-CoV-2 evolution. Previously developed methods for measuring selection coefficients and epistasis were improved, tested, and utilized to find the parameters. Ultimately, evidence was obtained in favor of the hypothesis that the virus crosses a fitness valley through a deleterious primary mutation linked to beneficial mutations and followed by secondary mutations, which compensate the fitness effect of primary mutation. Based on the data obtained, further research into the nature of variants of concern can be conducted to clarify the mechanism of their emergence and develop new vaccination strategies in the event of a recurrence of a situation similar to the COVID-19 pandemic. The following information technologies were used in this study: PyCharm, Unipro UGENE, MEGA11, MATLABR2023a, Circos, GitHub, GISAID, NCBI Virus, MAFFT.
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| ILC SPbPU Local Network | All |
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| Internet | Authorized users SPbPU |
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| Internet | Anonymous |
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