  Topological network motifs represent functional relationships within and
between regulatory and protein-protein interaction networks. Enriched motifs
often aggregate into self-contained units forming functional modules.
Theoretical models for network evolution by duplication-divergence mechanisms
and for network topology by hierarchical scale-free networks have suggested a
one-to-one relation between network motif enrichment and aggregation, but this
relation has never been tested quantitatively in real biological interaction
networks. Here we introduce a novel method for assessing the statistical
significance of network motif aggregation and for identifying clusters of
overlapping network motifs. Using an integrated network of transcriptional,
posttranslational and protein-protein interactions in yeast we show that
network motif aggregation reflects a local modularity property which is
independent of network motif enrichment. In particular our method identified
novel functional network themes for a set of motifs which are not enriched yet
aggregate significantly and challenges the conventional view that network motif
enrichment is the most basic organizational principle of complex networks.
