title: Metabolic networks are almost nonfractal: a comprehensive evaluation.
abstract: Network self-similarity or fractality are widely accepted as an important topological property of metabolic networks; however, recent studies cast doubt on the reality of self-similarity in the networks. Therefore, we perform a comprehensive evaluation of metabolic network fractality using a box-covering method with an earlier version and the latest version of metabolic networks and demonstrate that the latest metabolic networks are almost self-dissimilar, while the earlier ones are fractal, as reported in a number of previous studies. This result may be because the networks were randomized because of an increase in network density due to database updates, suggesting that the previously observed network fractality was due to a lack of available data on metabolic reactions. This finding may not entirely discount the importance of self-similarity of metabolic networks. Rather, it highlights the need for a more suitable definition of network fractality and a more careful examination of self-similarity of metabolic networks.
authors.affiliation: Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka 820-8502, Japan.
authors.forename: Kazuhiro
authors.initials: K
authors.lastname: Takemoto
mesh_terms: D017360:Arabidopsis / Q000378:metabolism; D004926:Escherichia coli / Q000378:metabolism; D017709:Fractals; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000378:metabolism