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Tuberculosis is killing millions of lives every year and on the blacklist of the most appalling public health problems. Recent findings suggest that secretory protein of Mycobacterium tuberculosis may serve the purpose of developing specific vaccines and drugs due to their antigenicity. Responding to global infectious disease, we focused on the identification of secretory proteins in Mycobacterium tuberculosis. A novel method called MycoSec was designed by incorporating g -gap dipeptide compositions into pseudo amino acid composition. Analysis of variance-based technique was applied in the process of feature selection and a total of 374 optimal features were obtained and used for constructing the final predicting model. In the jackknife test, MycoSec yielded a good performance with the area under the receiver operating characteristic curve of 0.93, demonstrating that the proposed system is powerful and robust. For user’s convenience, the web server MycoSec was established and an obliging manual on how to use it was provided for getting around any trouble unnecessary.

Identification of Secretory Proteins in Mycobacterium tuberculosis Using Pseudo Amino Acid Composition