Detecting hierarchical modularity in biological networks.
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.
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Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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*