Biology helps to construct weighted scale-free networks

2004/06/16 by A. Ramezanpour, A Ramezanpour · 5 citations
Engineering · Physics and Astronomy · #Bipartite graph #Complex Network Analysis Techniques #Complex network #Construct (python library) #Opinion Dynamics and Social Influence #Scale (ratio) #Scale-free network #Simple (philosophy) #Slime Mold and Myxomycetes Research #cond-mat.dis-nn #cond-mat.stat-mech

paper · pdf · doi:10.1209/epl/i2004-10194-5

published in Europhysics Letters (EPL) 68(2), 316-322 (Institute of Physics) · 15 pages, 7 figures, Revtex

arxiv created 2004/06/16 · openalex publication_date 2004/10/01 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05

Abstract

In this work we study a simple evolutionary model of bipartite networks whose evolution is based on the duplication of nodes. Using analytical results along with numerical simulation of the model, we show that the above evolutionary model results in weighted scale-free networks. Indeed we find that in the one-mode picture we have weighted networks with scale-free distributions for interesting quantities like the weights, the degrees and the weighted degrees of the nodes and the weights of the edges.

Citations

• Emergence of scaling in random networks
• Assortative Mixing in Networks
• Error and attack tolerance of complex networks
• Functional organization of the yeast proteome by systematic analysis of protein complexes
• Statistical mechanics of complex networks
• Evolution of the social network of scientific collaborations
• The Structure and Function of Complex Networks
• The architecture of complex weighted networks
• Random graphs with arbitrary degree distributions and their applications
• From the Cover: The structure of scientific collaboration networks