Three-Toed Sloth

Outsourced Heavy Flagella Blogging

I was going to blog about this paper,

Adrián López García de Lomana, Qasim K. Beg, G. de Fabritiis and Jordi Villà-Freixa, "Statistical Analysis of Global Connectivity and Activity Distributions in Cellular Networks", Journal of Computational Biology 17 (2010): 869--878, arxiv:1004.3138

Abstract: Various molecular interaction networks have been claimed to follow power-law decay for their global connectivity distribution. It has been proposed that there may be underlying generative models that explain this heavy-tailed behavior by self-reinforcement processes such as classical or hierarchical scale-free network models. Here we analyze a comprehensive data set of protein-protein and transcriptional regulatory interaction networks in yeast, an E. coli metabolic network, and gene activity profiles for different metabolic states in both organisms. We show that in all cases the networks have a heavy-tailed distribution, but most of them present significant differences from a power-law model according to a stringent statistical test. Those few data sets that have a statistically significant fit with a power-law model follow other distributions equally well. Thus, while our analysis supports that both global connectivity interaction networks and activity distributions are heavy-tailed, they are not generally described by any specific distribution model, leaving space for further inferences on generative models.

since they are very definitely not making the baby Gauss cry, but Aaron beat me to it, so you should just go read him.

(Study of the scholarly misconstruction of reality suggests that this will lead to at most a marginal reduction in the number of claims that biochemical networks follow power laws.)

Power Laws; Biology; Networks