Scale-free and biological networks follow a power law distribution p k / k Àa for the probability that a node is connected to k other nodes; the corresponding ranges for a (biological: 1 < a < 2; scale-free: 2 < a 6 3) yield a diverging variance for the connectivity k and lack of predictability for the average connectivity. Predictability can be achieved with the R enyi, Tsallis and Landsberg-Vedral extended entropies and corresponding ''disorders'' for correctly chosen values of the entropy index q. Escort distributions p k / k Àaq with q > 3=a also yield a nondiverging variance and predictability. It is argued that the Tsallis entropies may be the appropriate quantities for the study of scale-free and biological networks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.