Bayesian clustering of gene expression dynamic: an application

This paper describes an application of Caged (Cluster Analysis of Gene Expression Dynamics) to a data set of gene expression temporal profiles from Saccaromicys Cerevisiae. The goal of the analysis is to identify groups of genes with similar temporal patterns of expression during the cell cycle. We show that Caged can group gene expression temporal profiles into meaningful clusters and identifies novel genes with a putative role in the cell cycle.