2016
DOI: 10.1371/journal.pone.0159360
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Tracking the Antigenic Evolution of Foot-and-Mouth Disease Virus

Abstract: Quantifying and predicting the antigenic characteristics of a virus is something of a holy grail for infectious disease research because of its central importance to the emergence of new strains, the severity of outbreaks, and vaccine selection. However, these characteristics are defined by a complex interplay of viral and host factors so that phylogenetic measures of viral similarity are often poorly correlated to antigenic relationships. Here, we generate antigenic phylogenies that track the phenotypic evolu… Show more

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Cited by 34 publications
(54 citation statements)
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“…We do this through the inclusion of variables related to different properties of the branches of the phylogenetic tree. The reconstruction of phylogenetic trees is not the subject of this article, and therefore we use trees generated from the structural proteins of SAT1, SAT2 and H1N1 viruses presented by Reeve et al (2010Reeve et al ( , 2016 and Harvey et al (2016). Where possible, for each of the branches we include variables related to the effect of the challenge and protective strains, as well as to account for unknown antigenic effects; see Section 6 of the supplementary details for more information.…”
Section: Datamentioning
confidence: 99%
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“…We do this through the inclusion of variables related to different properties of the branches of the phylogenetic tree. The reconstruction of phylogenetic trees is not the subject of this article, and therefore we use trees generated from the structural proteins of SAT1, SAT2 and H1N1 viruses presented by Reeve et al (2010Reeve et al ( , 2016 and Harvey et al (2016). Where possible, for each of the branches we include variables related to the effect of the challenge and protective strains, as well as to account for unknown antigenic effects; see Section 6 of the supplementary details for more information.…”
Section: Datamentioning
confidence: 99%
“…Originally Reeve et al (2010) analysed the original SAT1 dataset (Sect. 4.2) and Reeve et al (2016) investigated an extended version of this dataset (Sect. 4.3).…”
Section: Real Data With Partial Ground Truthmentioning
confidence: 99%
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