The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Universality in network dynamics
Open accessAbstract
Despite significant advances in characterizing the structural properties of complex networks, a mathematical framework that uncovers the universal properties of the interplay between the topology and the dynamics of complex systems continues to elude us. Here we develop a self-consistent theory of dynamical perturbations in complex systems, allowing us to systematically separate the contribution of the network topology and dynamics. The formalism covers a broad range of steady-state dynamical processes and offers testable predictions regarding the system’s response to perturbations and the development of correlations. It predicts several distinct universality classes whose characteristics can be derived directly from the continuum equation governing the system’s dynamics and which are validated on several canonical network-based dynamical systems, from biochemical dynamics to epidemic spreading. Finally, we collect experimental data pertaining to social and biological systems, demonstrating that we can accurately uncover their universality class even in the absence of an appropriate continuum theory that governs the system’s dynamics. Models for the topology or dynamics of various networks abound, but until now, there has been no single universal framework for complex networks that can separate factors contributing to the topology and dynamics of networks across biological and social systems.
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Cites
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Yan, G., Tsekenis, G., Barzel, B., Slotine, J.-J., Liu, Y.-Y., & Barabási, A.-L. (2015) · Nature Physics · doi:10.1038/nphys3422 · Cited by 279
Self-citationPyrkov, T. V., Avchaciov, K., Tarkhov, A. E., Menshikov, L. I., Gudkov, A. V., & Fedichev, P. O. (2021) · Nature Communications · doi:10.1038/s41467-021-23014-1 · Cited by 139
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Metadata
- Authors
- Barzel, B., & Barabási, A.-L.
- Venue
- Nature Physics
- Published
- 2013-09-08
- Volume
- 9
- Issue
- 10
- Pages
- 673-681
- ISSN
- 1745-2473 (ISSN-L)
- 1745-2481
- OpenAlex
- W2101378420
- Cited by
- 396
- References
- 57
- FWCI
- 16.74
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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