title: Spectral analysis of deformed random networks.
abstract: We study spectral behavior of sparsely connected random networks under the random matrix framework. Subnetworks without any connection among them form a network having perfect community structure. As connections among the subnetworks are introduced, the spacing distribution shows a transition from the Poisson statistics to the Gaussian orthogonal ensemble statistics of random matrix theory. The eigenvalue density distribution shows a transition to the Wigner's semicircular behavior for a completely deformed network. The range for which spectral rigidity, measured by the Dyson-Mehta Delta3 statistics, follows the Gaussian orthogonal ensemble statistics depends upon the deformation of the network from the perfect community structure. The spacing distribution is particularly useful to track very slight deformations of the network from a perfect community structure, whereas the density distribution and the Delta3 statistics remain identical to the undeformed network. On the other hand the Delta3 statistics is useful for the larger deformation strengths. Finally, we analyze the spectrum of a protein-protein interaction network for Helicobacter, and compare the spectral behavior with those of the model networks.
authors.affiliation: Max-Planck Institute for the Physics of Complex Systems, Dresden, Germany. physarik@nus.edu.sg
authors.forename: Sarika
authors.initials: S
authors.lastname: Jalan
mesh_terms: D003198:Computer Simulation; D008954:Models, Biological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*; D015398:Signal Transduction / Q000502:physiology*; D012944:Social Support