  Genome-wide protein-protein interaction (PPI) data are readily available
thanks to recent breakthroughs in biotechnology. However, PPI networks of
extant organisms are only snapshots of the network evolution. How to infer the
whole evolution history becomes a challenging problem in computational biology.
In this paper, we present a likelihood-based approach to inferring network
evolution history from the topology of PPI networks and the duplication
relationship among the paralogs. Simulations show that our approach outperforms
the existing ones in terms of the accuracy of reconstruction. Moreover, the
growth parameters of several real PPI networks estimated by our method are more
consistent with the ones predicted in literature.
