General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2015 Vol.7(2): 145-148 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.946

Examining the Probability of the Critical Mutation of H5N8 by Comparing with H7N9 and H5N1 Using Apriori Algorithm and Support Vector Machine

Dae Young Kim, Hye-Jun Kim, Junhyeok Bae, and Taeseon Yoon

Abstract—In January, 2014, the outbreak of H5N8 in South Korea started in one duck farm. The representative outbreak of H5N8 is to turkey 1983 Ireland and to duck 2010 China. Obviously, people were concerned about whether this Influenza A virus is highly pathogenic or human transmissible. In this research to identify the probability of H5N8’s pathogenic rate, we will investigate its chance to have Cytokine Storm, a deadly attribute of Influenza A virus, by seeking similarity in glycoprotein amino acid sequence with H5N1, which has the same hemagglutinin subtype, using Support Vector Machine. In addition, to identify H5N8’s human transmissible possibility, we will compare the its year-on-year glycoprotein amino acid mutating trend with H7N9, which was previously known not to be transmissible to human but mutated to infect human, using Apriori Algorithm.

Index Terms—Apriori algorithm, H5N8, H5N1, H7N9, influenza A Virus, support vector machine.

Dae Young Kim, Hye-Jun Kim, Junhyeok Bae, and Taeseon Yoon are with the Natural Science Department, Hankuk Academy of Foreign Studies, South Korea (e-mail : dae8177@naver.com).

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Cite: Dae Young Kim, Hye-Jun Kim, Junhyeok Bae, and Taeseon Yoon, "Examining the Probability of the Critical Mutation of H5N8 by Comparing with H7N9 and H5N1 Using Apriori Algorithm and Support Vector Machine," International Journal of Computer Theory and Engineering vol. 7, no. 2, pp. 145-148, 2015.


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