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Some protein interaction data do not exhibit power law statistics
Author(s) -
Tanaka Reiko,
Yi Tau-Mu,
Doyle John
Publication year - 2005
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/j.febslet.2005.08.024
Subject(s) - scale (ratio) , power (physics) , power law , noise (video) , degree (music) , computer science , sampling (signal processing) , node (physics) , complex network , scale free network , statistics , law , data mining , econometrics , statistical physics , mathematics , artificial intelligence , physics , telecommunications , political science , quantum mechanics , detector , world wide web , acoustics , image (mathematics)
It has been claimed that protein–protein interaction (PPI) networks are scale‐free, and that identifying high‐degree “hub” proteins reveals important features of PPI networks. In this paper, we evaluate the claims that PPI node degree sequences follow a power law, a necessary condition for networks to be scale‐free. We provide two PPI network examples which clearly do not have power laws when analyzed correctly, and thus at least these PPI networks are not scale‐free. We also show that these PPI networks do appear to have power laws according to methods that have become standard in the existing literature. We explain the source of this error using numerically generated data from analytic formulas, where there are no sampling or noise ambiguities.