Metabolic networks are almost nonfractal: A comprehensive evaluation

TL;DR

This study reevaluates the fractality of metabolic networks, revealing that recent network data shows they are nearly nonfractal, challenging previous beliefs about their self-similarity.

Contribution

It provides a comprehensive analysis showing that updated metabolic networks are almost nonfractal, suggesting earlier findings were influenced by incomplete data.

Findings

Earlier networks appeared fractal, recent networks are not

Increased network density due to database updates explains previous fractality

Highlights need for better definitions of network fractality

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.