In Silico Vaccine Strain Prediction for Human Influenza Viruses.

Abstract:

:Vaccines preventing seasonal influenza infections save many lives every year; however, due to rapid viral evolution, they have to be updated frequently to remain effective. To identify appropriate vaccine strains, the World Health Organization (WHO) operates a global program that continually generates and interprets surveillance data. Over the past decade, sophisticated computational techniques, drawing from multiple theoretical disciplines, have been developed that predict viral lineages rising to predominance, assess their suitability as vaccine strains, link genetic to antigenic alterations, as well as integrate and visualize genetic, epidemiological, structural, and antigenic data. These could form the basis of an objective and reproducible vaccine strain-selection procedure utilizing the complex, large-scale data types from surveillance. To this end, computational techniques should already be incorporated into the vaccine-selection process in an independent, parallel track, and their performance continuously evaluated.

journal_name

Trends Microbiol

journal_title

Trends in microbiology

authors

Klingen TR,Reimering S,Guzmán CA,McHardy AC

doi

10.1016/j.tim.2017.09.001

subject

Has Abstract

pub_date

2018-02-01 00:00:00

pages

119-131

issue

2

eissn

0966-842X

issn

1878-4380

pii

S0966-842X(17)30206-8

journal_volume

26

pub_type

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