MRBF: A Method for Predicting HIV-1 Drug Resistance

This paper presents the MRBF network, a new algorithm adapted from the RBF network, to construct the classifiers for predicting phenotypic resistance on 6 protease inhibitors. The performance of the prediction was measured by 10-fold cross-validation. The results show that MRBF gives the lowest average mean square error (MSE) when compared with the traditional RBF network and multiple linear regression analysis (REG). Moreover, it provides the best average predictive accuracy when compared with HIVdb, REG, and Support Vector Machines (SVM).