The Blind Watchmaker Network: Scale-freeness and Evolution

TL;DR

This paper shows that cellular metabolic networks have a power-law degree distribution similar to random networks, suggesting evolution may preserve inherent randomness rather than specific structures, challenging traditional views on network development.

Contribution

It introduces the concept of the 'blind watchmaker' network, demonstrating that metabolic networks are statistically indistinguishable from random networks with scale-free properties, without assuming growth mechanisms.

Findings

Metabolic networks follow a power-law degree distribution with gamma >= 2.

Random networks can exhibit scale-free degree distributions similar to biological networks.

Evolutionary pathways may preserve inherent randomness rather than specific network structures.

Abstract

It is suggested that the degree distribution for networks of the cell-metabolism for simple organisms reflects an ubiquitous randomness. This implies that natural selection has exerted no or very little pressure on the network degree distribution during evolution. The corresponding random network, here termed the blind watchmaker network has a power-law degree distribution with an exponent gamma >= 2. It is random with respect to a complete set of network states characterized by a description of which links are attached to a node as well as a time-ordering of these links. No a priory assumption of any growth mechanism or evolution process is made. It is found that the degree distribution of the blind watchmaker network agrees very precisely with that of the metabolic networks. This implies that the evolutionary pathway of the cell-metabolism, when projected onto a metabolic network representation, has remained statistically random with respect to a complete set of network states. This suggests that even a biological system, which due to natural selection has developed an enormous specificity like the cellular metabolism, nevertheless can, at the same time, display well defined characteristics emanating from the ubiquitous inherent random element of Darwinian evolution. The fact that also completely random networks may have scale-free node distributions gives a new perspective on the origin of scale-free networks in general.