Klimm, FlorianBorge-Holthoefer, JavierWessel, NielsKurths, JürgenZamora-López, Gorka2016-02-192016-02-192014Klimm F, Borge-Holthoefer J, Wessel N, Kurths J, Zamora-Lopez G. Individual nodeʼs contribution to the mesoscale of complex networks. New Journal of Physics. 2014;16:125006. DOI: 10.1088/1367-2630/16/12/125006.1367-2630http://hdl.handle.net/10230/25903The analysis of complex networks is devoted to the statistical characterization of/nthe topology of graphs at different scales of organization in order to understand/ntheir functionality. While the modular structure of networks has become an/nessential element to better apprehend their complexity, the efforts to characterize/nthe mesoscale of networks have focused on the identification of the modules/nrather than describing the mesoscale in an informative manner. Here we propose/na framework to characterize the position every node takes within the modular/nconfiguration of complex networks and to evaluate their function accordingly./nFor illustration, we apply this framework to a set of synthetic networks,/nempirical neural networks, and to the transcriptional regulatory network of the/nMycobacterium tuberculosis.Wefind that the architecture of both neuronal and/ntranscriptional networks are optimized for the processing of multisensory information with the coexistence of well-de/nfined modules of specialized components and the presence of hubs conveying information from and to the/ndistinct functional domainsapplication/pdfengContent from this work may be used under the terms of the/nCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOIinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1088/1367-2630/16/12/125006Network metricsCommunity structureNeuronal networksGenetic regulatory networksinfo:eu-repo/semantics/openAccess