A network model with structured nodes

Abstract

We present a network model in which words over a specific alphabet, called {\it structures}, are associated to each node and undirected edges are added depending on some distance between different structures. It is shown that this model can generate, without the use of preferential attachment or any other heuristic, networks with topological features similar to biological networks: power law degree distribution, clustering coefficient independent from the network size, etc. Specific biological networks ({\it C. Elegans} neural network and {\it E. Coli} protein-protein interaction network) are replicated using this model.

arXiv commentmatch MRSA gene network not present because MRSA gene network still unpublished

References in corpus (6)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• Power-law distributions in empirical data
• Hierarchical organization of modularity in metabolic networks
• The large-scale organization of metabolic networks
• Infinite-Order Percolation and Giant Fluctuations in a Protein Interaction Network