Development of Neural Network for BLSOM Clustering of HA Genes of Avian Influenza Viruses Isolated in Guangdong Province

A neural network classification method,and a batch-learning self-organizing map(BLSOM),was established using trinucleotide and tetranucleotide in the hemagglutinin gene sequences of 25 avian influenza viruses isolated in Guangdong Province. Statistical analysis and normalization of the fragment numb...

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Published inAsian agricultural research Vol. 8; no. 11; pp. 101 - 104
Main Authors Tian, Chunjian, Luo, Qiong, Gao, Jiahui, Lin, Zhixiong, Yu, Haiqiong, Liu, Zhiling, Chen, Ru, Wu, Xiaowei
Format Journal Article
LanguageEnglish
Published Cranston Wu Chu (USA-China) Science and Culture Media Corporation 01.11.2016
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ISSN1943-9903

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Abstract A neural network classification method,and a batch-learning self-organizing map(BLSOM),was established using trinucleotide and tetranucleotide in the hemagglutinin gene sequences of 25 avian influenza viruses isolated in Guangdong Province. Statistical analysis and normalization of the fragment number were done and MATLAB function was used to simulate the human brain thinking for self-organizing learning. When the number of training steps was 100 and above,the strains could be successfully clustered. H1,H3,H5,H7 and H9 subtype strains fell within different classes,respectively,and the HA gene cluster map of H3N2 and H7N9strains was quite similar,suggesting that these strains shared the same origin; H5N1 strain was quite different in different years; H1N1 and H9N2 strains could be clustered into one group,indicating the natural recombinant variation in the two kinds of viruses,thereby providing a reference for high-risk strain screening and traceability.
AbstractList A neural network classification method,and a batch-learning self-organizing map(BLSOM),was established using trinucleotide and tetranucleotide in the hemagglutinin gene sequences of 25 avian influenza viruses isolated in Guangdong Province. Statistical analysis and normalization of the fragment number were done and MATLAB function was used to simulate the human brain thinking for self-organizing learning. When the number of training steps was 100 and above,the strains could be successfully clustered. H1,H3,H5,H7 and H9 subtype strains fell within different classes,respectively,and the HA gene cluster map of H3N2 and H7N9strains was quite similar,suggesting that these strains shared the same origin; H5N1 strain was quite different in different years; H1N1 and H9N2 strains could be clustered into one group,indicating the natural recombinant variation in the two kinds of viruses,thereby providing a reference for high-risk strain screening and traceability.
Author Chunjian TIAN Qiong LUO Jiahui GAO Zhixiong LIN Haiqiong YU Zhiling LIU Ru CHEN Xiaowei WU
AuthorAffiliation Guangdong Inspection and Quarantine Technology Center/Guangdong Provincial Key Laboratory of Animal and Plant and Food Import and Export Technology/AQSIQ State Key Laboratory of Avian Influenza
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Notes Chunjian TIAN;Qiong LUO;Jiahui GAO;Zhixiong LIN;Haiqiong YU;Zhiling LIU;Ru CHEN;Xiaowei WU;Guangdong Inspection and Quarantine Technology Center/Guangdong Provincial Key Laboratory of Animal and Plant and Food Import and Export Technology/AQSIQ State Key Laboratory of Avian Influenza
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Title Development of Neural Network for BLSOM Clustering of HA Genes of Avian Influenza Viruses Isolated in Guangdong Province
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