Structural distance and evolutionary relationship of networks

TL;DR

This paper introduces a method to quantify topological distances between networks of different sizes, revealing that network architectures are more similar within the same class and enabling the inference of evolutionary relationships from structural data.

Contribution

The paper presents a novel approach to measure structural distances between networks of varying sizes, aiding in understanding evolutionary relationships.

Findings

Networks within the same class have more similar architectures.

Structural distances can elucidate evolutionary relationships.

Method applied to 43 cellular networks across species.

Abstract

Evolutionary mechanism in a self-organized system cause some functional changes that force to adapt new conformation of the interaction pattern between the components of that system. Measuring the structural differences one can retrace the evolutionary relation between two systems. We present a method to quantify the topological distance between two networks of different sizes, finding that the architectures of the networks are more similar within the same class than the outside of their class. With 43 cellular networks of different species, we show that the evolutionary relationship can be elucidated from the structural distances.