The fractal nature of graphs has traditionally been investigated by using the network's nodes as the basic units. Here, instead, we propose to concentrate on the graph's edges, and introduce a practical and computationally not demanding method for revealing changes in the fractal behavior of networks, and particularly for allowing distinction between mono-fractal, quasi mono-fractal, and multi-fractal structures. We show that degree homogeneity plays a crucial role in determining the fractal nature of the underlying network, and report on six different protein-protein interaction networks along with their corresponding random networks. Our analysis allows to identify varying levels of complexity in the species.

Unveiling the multi-fractal structure of complex networks

Boccaletti S
2017

Abstract

The fractal nature of graphs has traditionally been investigated by using the network's nodes as the basic units. Here, instead, we propose to concentrate on the graph's edges, and introduce a practical and computationally not demanding method for revealing changes in the fractal behavior of networks, and particularly for allowing distinction between mono-fractal, quasi mono-fractal, and multi-fractal structures. We show that degree homogeneity plays a crucial role in determining the fractal nature of the underlying network, and report on six different protein-protein interaction networks along with their corresponding random networks. Our analysis allows to identify varying levels of complexity in the species.
2017
Istituto dei Sistemi Complessi - ISC
Complex networks
Fractal dimension
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/347077
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