Biology – Quantitative Biology – Molecular Networks
Scientific paper
2006-11-04
Mathematical Biosciences 208, 454 (2007)
Biology
Quantitative Biology
Molecular Networks
19 pages, 8 figures
Scientific paper
We propose a growing network model that consists of two tunable mechanisms: growth by merging modules which are represented as complete graphs and a fitness-driven preferential attachment. Our model exhibits the three prominent statistical properties are widely shared in real biological networks, for example gene regulatory, protein-protein interaction, and metabolic networks. They retain three power law relationships, such as the power laws of degree distribution, clustering spectrum, and degree-degree correlation corresponding to scale-free connectivity, hierarchical modularity, and disassortativity, respectively. After making comparisons of these properties between model networks and biological networks, we confirmed that our model has inference potential for evolutionary processes of biological networks.
Oosawa Chikoo
Takemoto Kazuhiro
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