Estimating the parameters of a model for protein-protein interaction graphs.

We find accurate approximations for the expected number of three-cycles and unchorded four-cycles under a stochastic distribution for graphs that has been proposed for modelling yeast two-hybrid protein-protein interaction networks. We show that unchorded four-cycles are characteristic motifs under this model and that the count of unchorded four-cycles in the graph is a reliable statistic on which to base parameter estimation. Finally, we test our model against a range of experimental data, obtain parameter estimates from these data and investigate possible improvements in the model. Characterization of this model lays the foundation for its use as a prior distribution in a Bayesian analysis of yeast two-hybrid networks that can potentially aid in identifying false-positive and false-negative results.