Bayesian clustering of gene expression dynamics: An application

Abstract

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 groups gene expression temporal profiles into meaningful clusters and identifies genes with a putative role in the cell cycle.