Identifying Critical Positions and Rules of Antigenic Drift for Influenza A/H3N2 Viruses
Pathogenic avian and human influenza virus often cause disastrous damage to human society and economics. Understanding antigenic drift of influenza viruses is an emergent issue for prophylaxis and vaccine development. In this study, we identified antigenic critical amino acid positions on hemagglutinin (HA) gene and rules for predicting antigenic variants. The information gain (IG) is applied to calculate the degree of association between the position mutation and antigenic drift. An amino acid with high IG at a specific position implied that this position is highly correlated to antigenic type change. The decision tree is applied to build model and discover rules for predicting antigenic variants. The decision tree can identify amino acid mutation rules that lead to the antigenic drift. The predicting accuracy of this model is 91.2％ which is better than related models. Most of these selected positions with high IG are located on epitope or surface on the HA structure. The position 145 with highest information gain could lead to antigenic cluster transition were verified. These results demonstrate that our approach is robust and is potential useful for vaccine development.
Vaccine development antigenic drift decision tree antigenic variants
Jhang-Wei Huang Chun-Chen Chen Jinn-Moon Yang
Institute of Bioinformatics, National Chiao Tung University Hsinchu, 30050, Taiwan
国际会议
上海
英文
249-252
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）