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

Authors :
Fonseca V
Libin PJK
Theys K
Faria NR
Nunes MRT
Restovic MI
Freire M
Giovanetti M
Cuypers L
Nowé A
Abecasis A
Deforche K
Santiago GA
Siqueira IC
San EJ
Machado KCB
Azevedo V
Filippis AMB
Cunha RVD
Pybus OG
Vandamme AM
Alcantara LCJ
de Oliveira T
Source :
PLoS neglected tropical diseases [PLoS Negl Trop Dis] 2019 May 08; Vol. 13 (5), pp. e0007231. Date of Electronic Publication: 2019 May 08 (Print Publication: 2019).
Publication Year :
2019

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. Available online: http://krisp.org.za/tools.php.<br />Competing Interests: Dr. Koen Deforche is one of the owners of the commercial company, EMWEB.

Details

Language :
English
ISSN :
1935-2735
Volume :
13
Issue :
5
Database :
MEDLINE
Journal :
PLoS neglected tropical diseases
Publication Type :
Academic Journal
Accession number :
31067235
Full Text :
https://doi.org/10.1371/journal.pntd.0007231