Literature DB >> 18999499

Two classes of bipartite networks: nested biological and social systems.

Enrique Burgos1, Horacio Ceva, Laura Hernández, R P J Perazzo, Mariano Devoto, Diego Medan.   

Abstract

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

Mesh:

Year:  2008        PMID: 18999499     DOI: 10.1103/PhysRevE.78.046113

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  2 in total

1.  Using graph theory to analyze biological networks.

Authors:  Georgios A Pavlopoulos; Maria Secrier; Charalampos N Moschopoulos; Theodoros G Soldatos; Sophia Kossida; Jan Aerts; Reinhard Schneider; Pantelis G Bagos
Journal:  BioData Min       Date:  2011-04-28       Impact factor: 2.522

2.  Asymmetric Relatedness from Partial Correlation.

Authors:  Carlos Saenz de Pipaon Perez; Andrea Zaccaria; Tiziana Di Matteo
Journal:  Entropy (Basel)       Date:  2022-03-03       Impact factor: 2.524

  2 in total

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