Predicting antigenic variants of H1N1 influenza virus based on epidemics and pandemics using a stacking model.

ABSTRACT: H1N1 is the earliest emerging subtype of influenza A viruses with available genomic sequences, has caused several pandemics and seasonal epidemics, resulting in millions of deaths and enormous economic losses. Timely determination of new antigenic variants is crucial for the vaccine selection and flu prevention. In this study, we chronologically divided the H1N1 strains into several periods in terms of the epidemics and pandemics. Computational models have been constructed to predict antigenic variants based on epidemic and pandemic periods. By sequence analysis, we demonstrated the diverse mutation patterns of HA1 protein on different periods and that an individual model built upon each period can not represent the variations of H1N1 virus. A stacking model was established for the predict

SUBMITTER: Yin R 

PROVIDER: S-EPMC6303045 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature