Individual nodeʼs contribution to the mesoscale of complex networks
The 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, t...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/25903 |
| Acceso en línea: | http://hdl.handle.net/10230/25903 http://dx.doi.org/10.1088/1367-2630/16/12/125006 |
| Access Level: | acceso abierto |
| Palabra clave: | Network metrics Community structure Neuronal networks Genetic regulatory networks |
| Sumario: | The 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 domains |
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