%0 Journal Article
%T Layer aggregation and reducibility of multilayer interconnected networks
%A M. De Domenico
%A V. Nicosia
%A A. Arenas
%A V. Latora
%J Computer Science
%D 2014
%I arXiv
%R 10.1038/ncomms7864
%X Many complex systems can be represented as networks composed by distinct layers, interacting and depending on each others. For example, in biology, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, with thousands of protein-protein interactions each. A fundamental open question is then how much information is really necessary to accurately represent the structure of a multilayer complex system, and if and when some of the layers can indeed be aggregated. Here we introduce a method, based on information theory, to reduce the number of layers in multilayer networks, while minimizing information loss. We validate our approach on a set of synthetic benchmarks, and prove its applicability to an extended data set of protein-genetic interactions, showing cases where a strong reduction is possible and cases where it is not. Using this method we can describe complex systems with an optimal trade--off between accuracy and complexity.
%U http://arxiv.org/abs/1405.0425v1