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A computational method for the identification of dengue, zika and chikungunya virus species and genotypes

2019-05-08Artigo científico Acesso aberto
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dc.contributor.authorFonseca, Vagner S.
dc.contributor.authorLibin, Pieter J. K.
dc.contributor.authorTheys, Kristof
dc.contributor.authorFaria, Nuno Rodrigues
dc.contributor.authorNunes, Márcio Roberto Texeira
dc.contributor.authorRestovic, Maria I.
dc.contributor.authorFreire, Murilo
dc.contributor.authorGiovanetti, Marta
dc.contributor.authorCuypers, Lize
dc.contributor.authorNowé, Ann
dc.contributor.authorAbecasis, AB
dc.contributor.authorDeforche, Koen
dc.contributor.authorSantiago, Gilberto A.
dc.contributor.authorde Siqueira, Isadora Cristina
dc.contributor.authorSan, Emmanuel J.
dc.contributor.authorMachado, Kaliane C.B.
dc.contributor.authorAzevedo, Vasco Ariston De Carvalho
dc.contributor.authorde Filippis, Ana Maria Bispo
dc.contributor.authorda Cunha, Rivaldo Venâncio
dc.contributor.authorPybus, Oliver George
dc.contributor.authorVandamme, AM
dc.contributor.authorAlcantara, L. C. J.
dc.contributor.authorde Oliveira, Túlio
dc.contributor.institutionTB, HIV and opportunistic diseases and pathogens (THOP)
dc.contributor.institutionGlobal Health and Tropical Medicine (GHTM)
dc.contributor.institutionInstituto de Higiene e Medicina Tropical (IHMT)
dc.contributor.pblPLOS - Public Library of Science
dc.date.accessioned2021-05-02T22:45:24Z
dc.date.available2021-05-02T22:45:24Z
dc.date.issued2019-05-08
dc.description.abstractIn recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent15
dc.format.extent1483805
dc.identifier.doi10.1371/journal.pntd.0007231
dc.identifier.issn1935-2727
dc.identifier.otherPURE: 15187331
dc.identifier.otherPURE UUID: 48d5256a-8736-4bd8-a9d7-1a24da475916
dc.identifier.otherScopus: 85066456449
dc.identifier.otherPubMed: 31067235
dc.identifier.otherPubMedCentral: PMC6527240
dc.identifier.urihttp://hdl.handle.net/10362/116728
dc.identifier.urlhttps://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0007231
dc.language.isoeng
dc.peerreviewedyes
dc.subjectComputer Science Applications
dc.subjectVirology
dc.subjectInfectious Diseases
dc.subjectGenetics
dc.subjectSDG 3 - Good Health and Well-being
dc.titleA computational method for the identification of dengue, zika and chikungunya virus species and genotypesen
dc.typejournal article
degois.publication.issue5
degois.publication.titlePLoS Neglected Tropical Diseases
degois.publication.volume13
dspace.entity.typePublication
rcaap.rightsopenAccess

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