Content-based network model with duplication and divergence

Yasemin Şengün and Ayşe Erzan

Physica A: Statistical Mechanics and its Applications, 2006, vol. 365, issue 2, 446-462

Abstract: 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.

Keywords: Networks; Scaling behavior; Genomics (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:365:y:2006:i:2:p:446-462

DOI: 10.1016/j.physa.2006.02.045

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