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dc.contributor.authorCacciabue, Marcoes
dc.contributor.authorMarcone, Débora N.es
dc.date.accessioned2023-05-16T13:49:12Z-
dc.date.available2023-05-16T13:49:12Z-
dc.date.issued2023-
dc.identifier.citationCacciabue, M., Marcone, D. N. Infinity: A fast machine learning-based application for human influenza A and B virus subtyping [en línea]. Influenza and Other Respiratory Viruses. 2023, 17(1). doi: 10.1111/irv.13096. Disponible en: https://repositorio.uca.edu.ar/handle/123456789/16351es
dc.identifier.issn1750-2659 (online)-
dc.identifier.issn1750-2640 (impreso)-
dc.identifier.urihttps://repositorio.uca.edu.ar/handle/123456789/16351-
dc.description.abstractInfluenza viruses are one of the main agents causing acute respiratory infections (ARI) in humans resulting in a large amount of illness and death globally.1,2 The influenza viruses classification is based on the nomenclature proposed by the World Health Organization (WHO)3 that is widely accepted and used by the medical and scientific communities throughout the world. Since the pandemic in 2009, two subtypes of human influenza A viruses, A(H1N1)pdm09 and A(H3N2), and two lineages of influenza B, B/Victoria and B/Yamagata, have been responsible for the vast majority of cases each year. Within each subtype and lineage, different clades and genetic groups were described to reflect the continuous viral evolution, driven by antigenic drift. The WHO Global Influenza Surveillance and Response System (GISRS) studies human influenza viruses from >110 countries, to monitor circulating strains, understand epidemiology and evolution, and contribute to verify the vaccine effectiveness and update its formulation each year.4,5 A growing number of laboratories and research centers is contributing to this initiative by sequencing the whole viral genome or the hemagglutinin (HA) gene from local strains...es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherJohn Wiley & Sonses
dc.rightsAcceso abierto*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.sourceInfluenza and Other Respiratory Viruses. Vol.17, No.1, 2023es
dc.subjectCLADOSes
dc.subjectGRUPOS GENETICOSes
dc.subjectHEMAGLUTININAes
dc.subjectINFLUENZAes
dc.subjectAPRENDIZAJE AUTOMÁTICOes
dc.subjectSECUENCIAes
dc.subjectSUBCLADOSes
dc.subjectSUBTIPIFICACIÓNes
dc.titleInfinity: A fast machine learning-based application for human influenza A and B virus subtypinges
dc.typeArtículoes
dc.identifier.doi10.1111/irv.13096-
uca.disciplinaMEDICINAes
uca.issnrd1es
uca.affiliationFil: Cacciabue, Marco. Instituto de Agrobiotecnología y Biología Molecular; Argentinaes
uca.affiliationFil: Cacciabue, Marco. Instituto Nacional de Tecnología Agropecuaria; Argentinaes
uca.affiliationFil: Cacciabue, Marco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes
uca.affiliationFil: Cacciabue, Marco. Departamento de Ciencias Básicas, Universidad Nacional de Luján; Argentinaes
uca.affiliationFil: Marcone, Débora N. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Bacteriología y Virología Molecular; Argentinaes
uca.affiliationFil: Marcone, Débora N. Pontificia Universidad Católica Argentina. Facultad de Ciencias Médicas; Argentinaes
uca.versionpublishedVersiones
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.languageiso639-1en-
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