Ranking in interconnected multilayer networks reveals versatile nodes
Open accessAbstract
The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating--or neglecting--the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in predicting their role in diffusive and congestion processes.
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Multi-layer or multiplex network models represent each omics layer as a distinct stratum and encode cross-layer relationships to capture inter-omic dependencies.
“More sophisticated strategies involve multi-layer or multiplex network models that represent each omics layer as a distinct stratum and encode cross-layer relationships to capture inter-omic dependencies308,309.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [308]
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- Authors
- De Domenico, M., Solé-Ribalta, A., Omodei, E., Gómez, S., & Arenas, A.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Universitat Rovira i Virgili (ES)
- Venue
- Nature Communications
- Published
- 2015-04-23
- Volume
- 6
- Issue
- 1
- Pages
- 6868-6868
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W1606375300
- Cited by
- 459
- References
- 65
- Citations by year
- 2026: 31 · 2025: 32 · 2024: 28 · 2023: 27 · 2022: 39 · 2021: 49 · 2020: 49 · 2019: 45 · 2018: 64 · 2017: 41 · 2016: 37 · 2015: 12 · 2014: 5
- FWCI
- 32.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nature Communications (publishedVersion, cc-by-sa)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by-sa)
- Funders
- James S. McDonnell Foundation
- European Commission (317614)
- Generalitat de Catalunya (2009-SGR-838)
- Institució Catalana de Recerca i Estudis Avançats
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Physical Sciences › Mathematics › Geometry and Topology › Graph theory and applications
- Keywords
- node centrality, multilayer networks, interconnected networks, node ranking, diffusion, congestion, information dissemination, epidemic spread, network cohesion
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