Mean field theory for biology inspired duplication-divergence network model.
Chaos
; 25(8): 083106, 2015 Aug.
Article
em En
| MEDLINE
| ID: mdl-26328557
ABSTRACT
The duplication-divergence network model is generally thought to incorporate key ingredients underlying the growth and evolution of protein-protein interaction networks. Properties of the model have been elucidated through numerous simulation studies. However, a comprehensive theoretical study of the model is lacking. Here, we derived analytic expressions for quantities describing key characteristics of the network-the average degree, the degree distribution, the clustering coefficient, and the neighbor connectivity-in the mean-field, large-N limit of an extended version of the model, duplication-divergence complemented with heterodimerization and addition. We carried out extensive simulations and verified excellent agreement between simulation and theory except for one partial case. All four quantities obeyed power-laws even at moderate network size ( Nâ¼10(4)), except the degree distribution, which had an additional exponential factor observed to obey power-law. It is shown that our network model can lead to the emergence of scale-free property and hierarchical modularity simultaneously, reproducing the important topological properties of real protein-protein interaction networks.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Mapas de Interação de Proteínas
/
Modelos Biológicos
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article