A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes

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2019xmlui.dri2xhtml.METS-1.0.item-files-viewOpen
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http://patua.iec.gov.br//handle/iec/3750xmlui.dri2xhtml.METS-1.0.item-author
Fonseca, Vagner
Libin, Pieter J. K
Theys, Kristof
Faria, Nuno R
Nunes, Márcio Roberto Teixeira
Restovic, Maria I
Freire, Murilo
Giovanetti, Marta
Cuypers, Lize
Nowé, Ann
Abecasis, Ana
Deforche, Koen
Santiago, Gilberto A
Siqueira, Isadora C. de
San, Emmanuel J
Machado, Kaliane C. B
Azevedo, Vasco
Bispo-de Filippis, Ana Maria
Cunha, Rivaldo Venâncio da
Pybus, Oliver G
Vandamme, Anne-Mieke
Alcântara, Luiz Carlos Junior
Oliveira, Tulio de
xmlui.dri2xhtml.METS-1.0.item-abstract
In 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.
xmlui.dri2xhtml.METS-1.0.item-citation
FONSECA, Vagner et al. A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes. PLoS Neglected Tropical Diseases, v. 13, n. 5, e0007231, p. 1-15, May 2019.xmlui.dri2xhtml.METS-1.0.item-decsPrimary
Arbovirus / classificaçãoDengue
Vírus Chikungunya
Zika virus
Biologia Computacional / métodos
Bases de Dados de Ácidos Nucleicos / utilização
Genótipo
Técnicas de Genotipagem / métodos
Surtos de Doenças
Monitoramento Epidemiológico
Variação Genética