ABSTRACT
ABSTRACT: This paper proposes a degree distribution function for protein-protein interaction networks. It is derived from modeling the protein-protein interaction network as a random duplication graph with sparse initial state, where the duplication particularly refers to the gene duplication that produces new proteins and grows the network. This degree distribution reveals some characteristics of protein-protein interaction networks: the majority of nodes are sparsely connected while highly connected proteins also exist; as the growth process continues, more and more highly connected proteins will be produced. Finally, we also show that compared to the widely used scale-free distribution, our degree distribution can fit the experimental data better.
