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dc.contributor.authorForghani, M.en
dc.contributor.authorKovalev, S.en
dc.contributor.authorKhachay, M.en
dc.contributor.authorRamsay, E.en
dc.contributor.authorBolkov, M.en
dc.contributor.authorVasev, P.en
dc.date.accessioned2024-04-05T16:16:24Z-
dc.date.available2024-04-05T16:16:24Z-
dc.date.issued2023-
dc.identifier.citationForghani, 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/microorganisms11020324harvard_pure
dc.identifier.citationForghani, 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/microorganisms11020324apa_pure
dc.identifier.issn2076-2607-
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access, Gold, Green3
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85149022656&doi=10.3390%2fmicroorganisms11020324&partnerID=40&md5=24ac4d9c9779fd676da584bbb614e91d1
dc.identifier.otherhttps://www.mdpi.com/2076-2607/11/2/324/pdf?version=1676540780pdf
dc.identifier.urihttp://elar.urfu.ru/handle/10995/130234-
dc.description.abstractEarly 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.en
dc.description.sponsorshipRussian Foundation for Basic Research, РФФИ: 19-31-60025; Ministry of Education and Science of the Russian Federation, Minobrnauka: 075-02-2022-874en
dc.description.sponsorshipThe 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).en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherMDPIen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rightscc-byother
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/unpaywall
dc.sourceMicroorganisms2
dc.sourceMicroorganismsen
dc.subjectCLUSTERON APPROACHen
dc.subjectEPIDEMIOLOGYen
dc.subjectEVOLUTIONen
dc.subjectMONITORINGen
dc.subjectTBEV ANALYZERen
dc.titleIdentifying New Clusterons: Application of TBEV Analyzer 3.0en
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.type|info:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.3390/microorganisms11020324-
dc.identifier.scopus85149022656-
local.contributor.employeeForghani, M., N. N. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, 620108, Russian Federation, Institute of Natural Sciences and Mathematics, Ural Federal University, Yekaterinburg, 620075, Russian Federationen
local.contributor.employeeKovalev, S., Institute of Natural Sciences and Mathematics, Ural Federal University, Yekaterinburg, 620075, Russian Federationen
local.contributor.employeeKhachay, M., N. N. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, 620108, Russian Federationen
local.contributor.employeeRamsay, E., Saint Petersburg Pasteur Institute, Saint Petersburg, 197101, Russian Federationen
local.contributor.employeeBolkov, M., Institute of Immunology and Physiology, Yekaterinburg, 620049, Russian Federationen
local.contributor.employeeVasev, P., N. N. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, 620108, Russian Federationen
local.issue2-
local.volume11-
dc.identifier.wos000940605800001-
local.contributor.departmentN. N. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, 620108, Russian Federationen
local.contributor.departmentInstitute of Natural Sciences and Mathematics, Ural Federal University, Yekaterinburg, 620075, Russian Federationen
local.contributor.departmentSaint Petersburg Pasteur Institute, Saint Petersburg, 197101, Russian Federationen
local.contributor.departmentInstitute of Immunology and Physiology, Yekaterinburg, 620049, Russian Federationen
local.identifier.pure35511163-
local.description.order324-
local.identifier.eid2-s2.0-85149022656-
local.identifier.wosWOS:000940605800001-
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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