ArticleProceedings of the National Academy of Sciences of the United States of America2024
Hypernetwork modeling and topology of high-order interactions for complex systems.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Omnidirectional Interaction Networks Modulating Phenotypic Plasticity in the Gut Microbiota Towards Ulcerative Colitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Topology-Aware Deep Learning on Higher-Order Structures for Drug Response Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Exploring epigenome-proteome interactions underlying post-surgical progression of non-functioning pituitary adenomas using hypernetwork modelling.Journal of translational medicine · 2026Article
- Statistical learning of stochastic complex systems via the Yau-Yau nonlinear filter.Innovation (Cambridge (Mass.)) · 2026Article
- Graph statistics theory of individualized quantitative genetics under haplotype-resolved genome assembly.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- An omnigenic interactome model to chart the genetic architecture of individual plants.Horticulture research · 2026Article
- Topological data analysis and topological deep learning beyond persistent homology: a review.Artificial intelligence review · 2026Article
- Optimization Method for Robustness of Hypernetwork Communication with Integrated Structural Features.Entropy (Basel, Switzerland) · 2026Article
- Empirical evidence for structural balance theory in functional brain networks.Frontiers in network physiology · 2025Article
- Hypernetwork modeling and topology of high-order interactions for complex systems.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
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Authors and funding
12 authors.
Funding
Abstract
Interactions among the underlying agents of a complex system are not only limited to dyads but can also occur in larger groups. Currently, no generic model has been developed to capture high-order interactions (HOI), which, along with pairwise interactions, portray a detailed landscape of complex systems. Here, we integrate evolutionary game theory and behavioral ecology into a unified statistical mechanics framework, allowing all agents (modeled as nodes) and their bidirectional, signed, and weighted interactions at various orders (modeled as links or hyperlinks) to be coded into hypernetworks. Such hypernetworks can distinguish between how pairwise interactions modulate a third agent (active HOI) and how the altered state of each agent in turn governs interactions between other agents (passive HOI). The simultaneous occurrence of active and passive HOI can drive complex systems to evolve at multiple time and space scales. We apply the model to reconstruct a hypernetwork of hexa-species microbial communities, and by dissecting the topological architecture of the hypernetwork using GLMY homology theory, we find distinct roles of pairwise interactions and HOI in shaping community behavior and dynamics. The statistical relevance of the hypernetwork model is validated using a series of in vitro mono-, co-, and tricultural experiments based on three bacterial species.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.