Finding Correlated Mutations among RNA Segments in H3N2 Influenza Viruses

被引:0
作者
Shimada, Takaharu [2 ]
Hazemoto, Tatsuya [1 ,3 ]
makino, Shunsuke [2 ]
Hirata, Kouichi [1 ]
Ito, Kimihito [4 ]
机构
[1] Kyushu Inst Technol, Dept Artificial Intelligence & Biomed Informat, R&D Ctr, Kawazu 680-4, Iizuka, Fukuoka 8208502, Japan
[2] Kyushu Inst Technol, Grad Sch Comp Sci & Syst Engn, Iizuka, Fukuoka 8208502, Japan
[3] Kyushu Inst Technol, Dept Artificial Intelligence, Iizuka, Fukuoka 8208502, Japan
[4] Hokkaido Univ, Res Ctr Zoonosis Control, Sapporo, Hokkaido 0010020, Japan
来源
6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS | 2012年
基金
日本学术振兴会;
关键词
packaging signal; influenza viruses; correlated mutation; A VIRUS; VIRAL-RNA; PACKAGING SIGNALS; VIRIONS; REPLICATION; REGIONS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to capture a selective packaging mechanism among eight RNA segments in influenza A viruses, we assume that almost nucleotides in the positions of packaging signals must be simultaneously changed. In this paper, we formulate such positions as correlated mutations based on a joint entropy ratio, develop a method of finding all of them by using set enumeration with pruning and apply to nucleotide sequences among RNA segments in H3N2 influenza viruses.
引用
收藏
页码:1696 / 1701
页数:6
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