ArticleNature communications2024
Reconstructing higher-order interactions in coupled dynamical systems.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Hypernetworks induce stable hyperlocking.Nature communications · 2026Article
- Statistical learning of stochastic complex systems via the Yau-Yau nonlinear filter.Innovation (Cambridge (Mass.)) · 2026Article
- Mining higher-order triadic interactions.Nature communications · 2025Article
- Dysregulation of hair-strand-based elemental biodynamics in amyotrophic lateral sclerosis.EBioMedicine · 2025Article
- Integrating physics and topology in neural networks for learning rigid body dynamics.Nature communications · 2025Article
- Hypergraph reconstruction from dynamics.Nature communications · 2025Article
- Phocaeicola vulgatus shapes the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile.Cell host & microbe · 2025Article
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Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Higher-order interactions play a key role for the operation and function of a complex system. However, how to identify them is still an open problem. Here, we propose a method to fully reconstruct the structural connectivity of a system of coupled dynamical units, identifying both pairwise and higher-order interactions from the system time evolution. Our method works for any dynamics, and allows the reconstruction of both hypergraphs and simplicial complexes, either undirected or directed, unweighted or weighted. With two concrete applications, we show how the method can help understanding the complexity of bacterial systems, or the microscopic mechanisms of interaction underlying coupled chaotic oscillators.
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Registered trials
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