In this paper, an effective gene selection algorithm is proposed, which employs a two-sample distribution-free test statistics for evaluating the gene expression differences in the compared datasets. The focus of this study is in the analysis of activeness of genes on a certain disease using intrinsic information about corresponding dataset structure. The algorithm was evaluated on the Acute Lymphoblastic Leukemia (ALL) dataset.
