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Modeling for evolving biological networks with scale-free connectivity, hierarchical modularity, and disassortativity
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Modeling for evolving biological networks with scale-free connectivity, hierarchical modularity, and disassortativity
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Paper
Modeling for evolving biological networks with scale-free connectivity, hierarchical modularity, and disassortativity
2006
Overview
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.
Publisher
Cornell University Library, arXiv.org
Subject
