Genome-wide protein-protein interaction (PPI) data are readily availablethanks to recent breakthroughs in biotechnology. However, PPI networks ofextant organisms are only snapshots of the network evolution. How to infer thewhole evolution history becomes a challenging problem in computational biology.In this paper, we present a likelihood-based approach to inferring networkevolution history from the topology of PPI networks and the duplicationrelationship among the paralogs. Simulations show that our approach outperformsthe existing ones in terms of the accuracy of reconstruction. Moreover, thegrowth parameters of several real PPI networks estimated by our method are moreconsistent with the ones predicted in literature.
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