A new feature encoding scheme for HIV-1 protease cleavage site prediction

@article{Gk2012ANF,
  title={A new feature encoding scheme for HIV-1 protease cleavage site prediction},
  author={Murat G{\"o}k and Ahmet Turan {\"O}zcerit},
  journal={Neural Computing and Applications},
  year={2012},
  volume={22},
  pages={1757-1761}
}
HIV-1 protease has been the subject of intense research for deciphering HIV-1 virus replication process for decades. Knowledge of the substrate specificity of HIV-1 protease will enlighten the way of development of HIV-1 protease inhibitors. In the prediction of HIV-1 protease cleavage site techniques, various feature encoding techniques and machine learning algorithms have been used frequently. In this paper, a new feature amino acid encoding scheme is proposed to predict HIV-1 protease… CONTINUE READING

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Key Quantitative Results

  • The presented encoding scheme shows better performance with the accuracy of 95 % without any kind of parameter optimization for the SVMs.

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