Network motifs have been identified in a wide range of networks across many scientific disciplinesand and are suggested to be the basic building blocks of most complex networks. Nonetheless, many networks come with intrinsic and/or experimental uncertainties and should be treated as stochastic networks. The building blocks in these networks thus may also have stochastic properties. We studied stochastic network motifs derived from families of mutually similar but not necessarily identical patterns of interconnections, established a finite mixture model for stochastic networks, and developed an expectation-maximization algorithm for identifying stochastic network motifs.
— Rui Jiang, et al., Network motif identification in stochastic networks. Proc. Natl. Acad. Sci. USA, 103.

Complex networks are studied across many fields of science. Network motifs, patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks, have been discovered in networks from the World Wide Web to social networks and aresuggested to perform information processing, even though they describe very different elements in different networks. Motifs may thus define universal classes of networks and help us to uncover the basic building blocks of most networks.
— Alon, et al., Network motifs: simple building blocks of complex networks. Science, 300.