Structural reducibility of multilayer networks

Manlio De Domenico, Vincenzo Nicosia (), Alexandre Arenas () and Vito Latora
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Manlio De Domenico: Departament d’Enginyeria Informática i Matemátiques, Universitat Rovira I Virgili, Avda Paisos Catalans 26, Tarragona 43007, Spain
Vincenzo Nicosia: School of Mathematical Sciences, Queen Mary University of London
Alexandre Arenas: Departament d’Enginyeria Informática i Matemátiques, Universitat Rovira I Virgili, Avda Paisos Catalans 26, Tarragona 43007, Spain
Vito Latora: School of Mathematical Sciences, Queen Mary University of London

Nature Communications, 2015, vol. 6, issue 1, 1-9

Abstract: Abstract Many complex systems can be represented as networks consisting of distinct types of interactions, which can be categorized as links belonging to different layers. For example, a good description of the full protein–protein interactome requires, for some organisms, up to seven distinct network layers, accounting for different genetic and physical interactions, each containing thousands of protein–protein relationships. A fundamental open question is then how many layers are indeed necessary to accurately represent the structure of a multilayered complex system. Here we introduce a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph. We validate our approach on synthetic benchmarks and we show that the number of informative layers in some real multilayer networks of protein–genetic interactions, social, economical and transportation systems can be reduced by up to 75%.

Date: 2015
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DOI: 10.1038/ncomms7864

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