Inference of a Genetic Network with Use of a Hierarchical Clustering from a Large Amount of Gene Expression Data

Abstract

Advances in microarray techniques have enabled us to simultaneously monitor the expression levels of thousands or tens of thousands of genes under multiple conditions. Here, we present a novel method to analyze a large amount of gene expression profiles by the combination of the standard statistical techniques. The method is composed of two parts : the automatic determination of cluster boundaries in a hierarchical clustering and the following inference of a network by application of graphical Gaussian modeling. The feasibility of our method is discussed in terms of the biological knowledge of gene regulatory systems and the other analytical approaches.