In this analysis we use the biological process ontology developed by the Gene Ontology (GO) consortium [21,22], the GO annotations from EMBL-EBI [23] and hypothesize that the likelihood for a gene pair to be regulated in the same manner increases with the similarity of their GO description. GO analysis was proposed by [20] who applied it to find functional modules in E. coli. However, here a training set of gene/TF interactions is used instead of a gene-gene pair-based one. In particular, we use a preliminary E. coli TRN and transform the gene-gene scores to gene-TF scores. Each GO is structured as a directed acyclic graph. The GO similarity score between two gene products is based on the number of shared ancestors. As a gene product might be assigned with multiple GO terms, we seek the maximum similarity score between all possible combinations. Let gene i and gene j be assigned hi and hj GO terms, respectively. Then the GO similarity for the gene (i, j) pair is taken to be the maximum number of shared ancestors for all combinations of the hi and hj.