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A Probabilistic Peptide Machine for Predicting Hepatitis C Virus Protease Cleavage Sites

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1 Author(s)
Zheng Rong Yang ; Univ. of Exeter, Exeter

Although various machine learning approaches have been used for predicting protease cleavage sites, constructing a probabilistic model for these tasks is still challenging. This paper proposes a novel algorithm termed as a probabilistic peptide machine where estimating probability density functions and constructing a classifier for predicting protease cleavage sites are combined into one process. The simulation based on experimentally determined Hepatitis C virus (HCV) protease cleavage data has demonstrated the success of this new algorithm.

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Information Technology in Biomedicine, IEEE Transactions on  (Volume:11 ,  Issue: 5 )