Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo; Institute for Advanced Biosciences, Keio University; and Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency
For correspondence: Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha 5-1-5 CB05, Kashiwa, 277-8561. Tel: +81-4-7136-3988, Fax: +81-4-7136-4074, E-mail: firstname.lastname@example.org
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.