Graph based unsupervised feature selection for microarray data

Gene selection is an important step in microarray data analysis. In this paper we present an unsupervised feature selection technique for this purpose. The method constructs multiview graph based representation of samples using expression values gene sub clusters. Such individual views are further clustered using graph clustering techniques. We evaluate our technique using classification accuracies obtained from selecting representative genes from each such clusters.