  We examine the modular structure of the metabolic network when combined with
the regulatory network representing direct regulation of enzymes by small
metabolites in E.coli. In order to identify the modular structure we introduce
clustering algorithm based on a novel vertex similarity measure for bipartite
graphs. We also apply a standard module identification method based on
simulated annealing. Both methods identify the same modular core each of them
with different resolution. We observe slight but still statistically
significant increase of modularity after regulatory interactions addition.
Enrichment of the metabolic network with the regulatory information leads to
identification of new functional modules, which cannot be detected in the
metabolic network only. Regulatory loops in the modules are the source of their
self-control, i.e. autonomy, and allow to make hypothesis about module
function. This study demonstrates that incorporation of regulatory information
is important component in defining functional units of the metabolic network.
