Selecting Genes with Dissimilar Discrimination Strength for Sample Class Prediction

Abstract

them all in classication is largely redundant. Furthermore, these selected genes can prevent the consideration of other individually-less but collectively-more dieren tially expressed genes. We propose to cluster genes in terms of their class discrimination strength and to limit the number of selected genes per cluster. By combining this idea with several existing single gene scoring methods, we show by experiments on two cancer microarray datasets that our methods identify gene subsets which collectively have signican tly higher classication accuracies.