Identifying New Clusterons: Application of TBEV Analyzer 3.0
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
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Identifying New Clusterons: Application of TBEV Analyzer 3.0
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| Автор |
Forghani, M.
Kovalev, S. Khachay, M. Ramsay, E. Bolkov, M. Vasev, P. |
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| Тематика |
CLUSTERON APPROACH
EPIDEMIOLOGY EVOLUTION MONITORING TBEV ANALYZER |
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| Описание |
Early knowledge about novel emerging viruses and rapid determination of their characteristics are crucial for public health. In this context, development of theoretical approaches to model viral evolution are important. The clusteron approach is a recent bioinformatics tool which analyzes genetic patterns of a specific E protein fragment and provides a hierarchical network structure of the viral population at three levels: subtype, lineage, and clusteron. A clusteron is a group of strains with identical amino acid (E protein fragment) signatures; members are phylogenetically closely related and feature a particular territorial distribution. This paper announces TBEV Analyzer 3.0, an analytical platform for rapidly characterizing tick-borne encephalitis virus (TBEV) strains based on the clusteron approach, workflow optimizations, and simplified parameter settings. Compared with earlier versions of TBEV Analyzer, we provide theoretical and practical enhancements to the platform. Regarding the theoretical aspect, the model of the clusteron structure, which is the core of platform analysis, has been updated by analyzing all suitable TBEV strains available in GenBank, while the practical enhancements aim at improving the platform’s functionality. Here, in addition to expanding the strain sets of prior clusterons, we introduce eleven novel clusterons through our experimental results, predominantly of the European subtype. The obtained results suggest effective application of the proposed platform as an analytical and exploratory tool in TBEV surveillance. © 2023 by the authors.
Russian Foundation for Basic Research, РФФИ: 19-31-60025; Ministry of Education and Science of the Russian Federation, Minobrnauka: 075-02-2022-874 The reported study was funded by RFBR, project number 19-31-60025. Michael Khachay was funded by the Ural Mathematical Center with the financial support of the Ministry of Education and Science of the Russian Federation (Agreement number 075-02-2022-874). |
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| Дата |
2024-04-05T16:16:24Z
2024-04-05T16:16:24Z 2023 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) |info:eu-repo/semantics/publishedVersion |
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| Идентификатор |
Forghani, M, Kovalev, S, Khachay, M, Ramsay, E, Bolkov, M & Vasev, P 2023, 'Identifying New Clusterons: Application of TBEV Analyzer 3.0', Microorganisms, Том. 11, № 2, 324. https://doi.org/10.3390/microorganisms11020324
Forghani, M., Kovalev, S., Khachay, M., Ramsay, E., Bolkov, M., & Vasev, P. (2023). Identifying New Clusterons: Application of TBEV Analyzer 3.0. Microorganisms, 11(2), [324]. https://doi.org/10.3390/microorganisms11020324 2076-2607 Final All Open Access, Gold, Green https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149022656&doi=10.3390%2fmicroorganisms11020324&partnerID=40&md5=24ac4d9c9779fd676da584bbb614e91d https://www.mdpi.com/2076-2607/11/2/324/pdf?version=1676540780 http://elar.urfu.ru/handle/10995/130234 10.3390/microorganisms11020324 85149022656 000940605800001 |
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| Язык |
en
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by https://creativecommons.org/licenses/by/4.0/ |
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| Формат |
application/pdf
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MDPI
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| Источник |
Microorganisms
Microorganisms |
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