Identify Secretory Protein of Malaria Parasite with Modified Quadratic Discriminant Algorithm and Amino Acid Composition
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Malaria parasite secretes various proteins in infected red blood cell for its growth and survival. Thus identification of these secretory proteins is important for developing vaccine or drug against malaria. In this study, the modified method of quadratic discriminant analysis is presented for predicting the secretory proteins. Firstly, 20 amino acids are divided into five types according to the physical and chemical characteristics of amino acids. Then, we used five types of amino acids compositions as inputs of the modified quadratic discriminant algorithm. Finally, the best prediction performance is obtained by using 20 amino acid compositions, the sensitivity of 96 %, the specificity of 92 % with 0.88 of Mathew’s correlation coefficient in fivefold cross-validation test. The results are also compared with those of existing prediction methods. The compared results shown our method are prominent in the prediction of secretory proteins.
KeywordsSecretory proteins Modified quadratic discriminant algorithm Amino acid composition Prediction performance
The author is grateful to the anonymous reviewers for their valuable suggestions and comments, which have led to the improvement of this paper. The work was supported by National Science foundation of China (No. 31360206) and the project of “prairie excellence” engineering in Inner Mongolia and the Inner Mongolia autonomous region higher school science and technology research projects (No. NJZY067) and Basic Science of Inner Mongolia Agriculture University Research Fund (No. JC2013004).
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