Article
A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes
Registro en:
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, p. 1-15, 2019.
1935-2727
10.1371/journal.pntd.0007231
Autor
Fonseca, Vagner
Libin, Pieter J. K.
Theys, Kristof
Faria, Nuno Rodrigues
Nunes, Marcio 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 Caldas de Brito
Azevedo, Vasco
Filippis, Ana Maria Bispo de
Cunha, Rivaldo Venâncio da
Pybus, Oliver G.
Vandamme, Anne-Mieke
Alcantara, Luiz Carlos Junior
Oliveira, Tulio de
Resumen
Funding: Supported by a research Flagship grant from the South African Medical Re-search Council (MRC-RFA-UFSP-01-2013/UKZN HIVEPI), a Royal Society Newton Advanced Fellowship (TdO), the VIROGENESIS project receives funding from the European Union’s Horizon 2020 Research and Innovation Programme (under Grant Agreement no. 634650) and the National Institutes of Health Common Fund, grant number U24HG006941.
Pieter Libin was supported by a PhD grant of the FWO (Fonds Wetenschappelijk Onderzoek -Vlaanderen). This work was supported by Decit/SCTIE/MoH and CNPq (440685/2016-8 and 440856/2016-7); by CAPES (88887.130716/2016-00, 88881.130825/2016-00 and 88887.130823/2016-00); and by EU’s Horizon 2020 Programme through ZIKAlliance (PRES-005-FEX-17-4-2-33). Ana Abecasis was supported by Fundação para a Ciência e Tecnologia (FCT) through funds to
GHTM-UID/Multi/04413/2013. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
manuscript. Competing interests: Dr. Koen Deforche is one of
the owners of the commercial company, EMWEB. 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. Available online: http://krisp.org.za/tools.php.
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