Abstract:

This paper introduces a model of cluster analysis on the gene expression data. By processing signaltonoise ratio, comparing the cluster analysis results and searching the corresponding markers, it offers an efficient method to postanalyze the gene expression data and discover different genes. Gene expression data of a diabetic mouse are analyzed, and significance of this analysis obtained, which facilitates technical support to rapid and early clinical diagnosis of diabetes.

Key words: gene expression profiles; process model; cluster analysis; different gene