Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/130234
Title: Identifying New Clusterons: Application of TBEV Analyzer 3.0
Authors: Forghani, M.
Kovalev, S.
Khachay, M.
Ramsay, E.
Bolkov, M.
Vasev, P.
Issue Date: 2023
Publisher: MDPI
Citation: 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
Abstract: 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.
Keywords: CLUSTERON APPROACH
EPIDEMIOLOGY
EVOLUTION
MONITORING
TBEV ANALYZER
URI: http://elar.urfu.ru/handle/10995/130234
Access: info:eu-repo/semantics/openAccess
cc-by
License text: https://creativecommons.org/licenses/by/4.0/
SCOPUS ID: 85149022656
WOS ID: 000940605800001
PURE ID: 35511163
ISSN: 2076-2607
DOI: 10.3390/microorganisms11020324
metadata.dc.description.sponsorship: 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).
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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