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Artigo
A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes
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...
Autor principal: | Fonseca, Vagner |
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Outros Autores: | Libin, Pieter J. K, Theys, Kristof, Faria, Nuno R, Nunes, M?rcio Roberto Teixeira, Restovic, Maria I, Freire, Murilo, Giovanetti, Marta, Cuypers, Lize, Now?, 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 Ven?ncio da, Pybus, Oliver G, Vandamme, Anne-Mieke, Alc?ntara, Luiz Carlos Junior, Oliveira, Tulio de |
Grau: | Artigo |
Idioma: | eng |
Publicado em: |
Public Library of Science
2019
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Assuntos: | |
Acesso em linha: |
http://patua.iec.gov.br//handle/iec/3750 |
Resumo: |
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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. |