Using multiple linear regression and physicochemical changes of amino acid mutations to predict antigenic variants of influenza A/H3N2 viruses.

@article{Cui2014UsingML,
  title={Using multiple linear regression and physicochemical changes of amino acid mutations to predict antigenic variants of influenza A/H3N2 viruses.},
  author={HaiBo Cui and Xiaomei Wei and Yu Huang and B. Y.-K. Hu and Yaping Fang and Jia Yu Wang},
  journal={Bio-medical materials and engineering},
  year={2014},
  volume={24 6},
  pages={3729-35}
}
Among human influenza viruses, strain A/H3N2 accounts for over a quarter of a million deaths annually. Antigenic variants of these viruses often render current vaccinations ineffective and lead to repeated infections. In this study, a computational model was developed to predict antigenic variants of the A/H3N2 strain. First, 18 critical antigenic amino acids in the hemagglutinin (HA) protein were recognized using a scoring method combining phi (ϕ) coefficient and information entropy. Next, a… CONTINUE READING