title: Detecting hierarchical modularity in biological networks.
abstract: Spatially or chemically isolated modules that carry out discrete functions are considered fundamental building blocks of cellular organization. However, detecting them in highly integrated biological networks requires a thorough understanding of the organization of these networks. In this chapter I argue that many biological networks are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units. On top of a scale-free degree distribution, these networks show a power law scaling of the clustering coefficient with the node degree, a property that can be used as a signature of hierarchical organization. As a case study, I identify the hierarchical modules within the Escherichia coli metabolic network, and show that the uncovered hierarchical modularity closely overlaps with known metabolic functions.
authors.affiliation: Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
authors.forename: Erzsébet
authors.initials: E
authors.lastname: Ravasz
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism / Q000502:physiology; D053263:Gene Regulatory Networks / Q000502:physiology*; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*