Finding correlated mutations among RNA segments in H3N2 influenza viruses

Author

Shimada, Toshikazu ; Hazemoto, T. ; Makino, Shigeru ; Hirata, Kazufumi ; Ito, Kei

Author_Institution

Grad. Sch. of Comput. Sci. & Syst. Eng., Kyushu Inst. of Technol., Iizuka, Japan

fYear

2012

fDate

20-24 Nov. 2012

Firstpage

1696

Lastpage

1701

Abstract

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.

Keywords

biology computing; entropy; microorganisms; molecular biophysics; set theory; signal processing; H3N2 influenza virus; RNA segment; correlated mutation; joint entropy ratio; nucleotide sequence; packaging signal; selective packaging mechanism; set enumeration; correlated mutation; influenza viruses; packaging signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on

Conference_Location

Kobe

Print_ISBN

978-1-4673-2742-8

Type

conf

DOI

10.1109/SCIS-ISIS.2012.6505354

Filename

6505354

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2008300