  Subgraphs and cycles are often used to characterize the local properties of
complex networks. Here we show that the subgraph structure of real networks is
highly time dependent: as the network grows, the density of some subgraphs
remains unchanged, while the density of others increase at a rate that is
determined by the network's degree distribution and clustering properties. This
inhomogeneous evolution process, supported by direct measurements on several
real networks, leads to systematic shifts in the overall subgraph spectrum and
to an inevitable overrepresentation of some subgraphs and cycles.

Disordered Systems and Neural Networks;Statistical Mechanics