Recently, several works have approached the HIV-1 protease specificity problem by applying techniques from machine learning. In this work, an encoding scheme based on the BLOSUM50 matrix is investigated. We show that combining a linear discriminant classifier and radial basis function Support Vector Machine we obtain performance higher than previously published in the literature.
Nanni, L., Lumini, A. (2006). A reliable method for HIV-1 Protease Cleavage Site Prediction. NEUROCOMPUTING, 69, 838-841 [10.1016/j.neucom.2005.09.004].
A reliable method for HIV-1 Protease Cleavage Site Prediction
NANNI, LORIS;LUMINI, ALESSANDRA
2006
Abstract
Recently, several works have approached the HIV-1 protease specificity problem by applying techniques from machine learning. In this work, an encoding scheme based on the BLOSUM50 matrix is investigated. We show that combining a linear discriminant classifier and radial basis function Support Vector Machine we obtain performance higher than previously published in the literature.File in questo prodotto:
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