Title :
The prediction of pathogenicity of the influenza virus based on HA protein sequences
Author :
Yi Zhang ; Shili Jia ; Haiyun Huang
Author_Institution :
Dept. of Math., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
The influenza A virus has higher pathogenicity than influenza B virus, the difference is related with influenza virus HA proteins. In this paper, we try to find the mathematic relationship between the HA protein sequences and virus pathogenicity, it may benefit the influenza diagnosis. We download HA protein sequences from NCBI, and present the position-specific difference between HA proteins of influenza A and B virus by multi-sequence alignment. Then, we use a Fisher discriminant algorithm to predict pathogenicity of influenza virus with k-mer frequency of HA protein sequences. Moreover, we found the abundance of a class of amino acids is related with high pathogenicity.
Keywords :
RNA; bioinformatics; genomics; microorganisms; proteins; statistical analysis; Fisher discriminant algorithm; HA protein sequences; RNA genome; amino acids; bioinformatics method; influenza A virus pathogenicity prediction; influenza B virus pathogenicity prediction; influenza diagnosis; k-mer frequency; mathematic relationship; multisequence alignment; position-specific difference; Abstracts; Bioinformatics; Equations; Genomics; Influenza; Proteins; Vectors; Influenza virus; Non-conservative sites; Pathogenicity; Prediction;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
Print_ISBN :
978-1-4799-4216-9
DOI :
10.1109/ICMLC.2014.7009684
