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 [A. Wagner, Proc. Natl. Acad. Sci. {\bf 91}, 4387 (1994)] 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 exponents $\gamma_1$ and $\gamma_2=\gamma_1-1/2$ of the Balcan-Erzan model turn out to be robust under duplication and point mutations, but get modified in the presence of splitting and merging of strings. The clustering coefficient as a function of the degree, $C(d)$, is found, for the Balcan-Erzan model, to behave in a way qualitatively similar to the out-degree distribution, however with a very small exponent $\alpha_1= 1-\gamma_1$ and an envelope for the oscillatory part, which is essentially flat, thus $\alpha_2= 0$. Under duplication and mutations including splitting and merging of strings, $C(d)$ is found to decay exponentially. 
Yasemin Sengun and Ayse Erzan