Content-based network model with duplication and divergence

We construct a minimal content-based realization of the duplication and divergence model of genomic networks introduced by Wagner [Proc. Natl. Acad. Sci. 91 (1994) 4387] and investigate the scaling properties of the directed degree distribution and clustering coefficient. We find that the content-based network exhibits crossover between two scaling regimes, with log-periodic oscillations for large degrees. These features are not present in the original gene duplication model, but inherent in the content-based model of Balcan and Erzan. The scaling form of the degree distribution of the content-based model turns out to be robust under duplication and divergence, with some re-adjustment of the scaling exponents, while the out-clustering coefficient goes over from a weak power-law dependence on the degree, to an exponential decay under mutations which include splitting and merging of strings.