title: Scale-freeness and biological networks.
abstract: The notion of scale-freeness and its prevalence in both natural and artificial networks have recently attracted much attention. The concept of scale-freeness is enthusiastically applied to almost any conceivable network, usually with affirmative conclusions. Well-known scale-free examples include the internet, electric lines among power plants, the co-starring of movie actors, the co-authorship of researchers, food webs, and neural, protein-protein interactional, genetic, and metabolic networks. The purpose of this review is to clarify the relationship between scale-freeness and power-law distribution, and to assess critically the previous related works, especially on biological networks. In addition, I will focus on the close relationship between power-law distribution and lognormal distribution to show that power-law distribution is not a special characteristic of natural selection.
authors.affiliation: Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha 5-1-5 CB05, Kashiwa. arita@k.u-tokyo.ac.jp
authors.forename: Masanori
authors.initials: M
authors.lastname: Arita
mesh_terms: D019295:Computational Biology; D020407:Internet; D008954:Models, Biological; D016571:Neural Networks, Computer; D011336:Probability