Feature genes selection of adult ALL microarray data with affinity propagation clustering

Abstract

Microarray data analysis approach has been became a widely used tool for disease detection. It uses tens of thousands of genes as input dimension that would be a huge computational problem for data analysis. In this paper, we proposed to apply affinity propagation (AP) clustering for feature genes selection of adult acute Lymphoblastic Leukemias (ALL) microarray data. That is, feature genes can be finding out according to the adjustable the number of cluster in AP clustering. AP Clustering is a new grouping method by passing messages between data points, AP clustering can to reduce dimension on each sample without known the number of cluster in advance. Finally, these results under the specific genes with AP clustering can provide learning in classification and prediction.