The topological relationship between the large-scale attributes and local interaction patterns of complex networks.
Recent evidence indicates that the abundance of recurring elementary interaction patterns in complex networks, often called subgraphs or motifs, carry significant information about their function and overall organization. Yet, the underlying reasons for the variable quantity of different subgraph types, their propensity to form clusters, and their relationship with the networks' global organization remain poorly understood. Here we show that a network's large-scale topological organization and its local subgraph structure mutually define and predict each other, as confirmed by direct measurements in five well studied cellular networks. We also demonstrate the inherent existence of two distinct classes of subgraphs, and show that, in contrast to the low-density type II subgraphs, the highly abundant type I subgraphs cannot exist in isolation but must naturally aggregate into subgraph clusters. The identified topological framework may have important implications for our understanding of the origin and function of subgraphs in all complex networks.
Vázquez
A
A
Department of Physics and Center for Complex Network Research, University of Notre Dame, Notre Dame, IN 46556, USA.
Dobrin
R
R
Sergi
D
D
Eckmann
J-P
JP
Oltvai
Z N
ZN
Barabási
A-L
AL
D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D004926:Escherichia coli / Q000502:physiology*; D008660:Metabolism; D008954:Models, Biological; D008962:Models, Theoretical; D011506:Proteins / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000502:physiology*; D014158:Transcription, Genetic
D011506:Proteins