Clustering and Functional Annotation over ChlamyNet

The goal of clustering techniques when applied to gene co-expression data consists on identifying disjoint groups or clusters of genes with highly similar expression profiles. In our study we identified nine different clusters. Since the genes in each cluster are co-expressed throughout diverse physiological conditions they are likely involved in the same biological processes. In order to determine the biological processes in which each gene cluster is significantly involved we performed Gene Ontology (GO) term enrichment.