Characterization of degree frequency distribution in protein interaction networks

SEBASTIÁN A. ROMANO; MANUEL C. EGUIA

La Serena

Conferencia; XIV Conference on Nonequilibrium Statistical Mechanics and Nonlinear Physics; 2004

We analyze the degree frequency distribution in the yeast protein interaction network by studying a previously proposed duplication network model. This model correctly predicts the observed degree distribution (a power-law for large degree values and a departure from this behavior for small degree). We numerically and analitically characterize this distribution as a mixture of random and power-law behavior,and make a comparative study of the robustness of the network model against realistic perturbations. We conclude that the particular distribution observed in both the model and the experimental data has many advantages in terms of dynamical and topological robustness and could have emerged in the evolutionary history as a sort of compromise between purely deterministic and random underlying mechanisms of network growth.