Hypernetwork modeling and topology of high- order interactions for complex systems

• 成果类型: Article
• 署名作者: Feng, Li; Gong, Huiying; Zhang, Shen; Liu, Xiang; Wang, Yu; Che, Jincan; Dong, Ang; Griffin, Christopher H.; Gragnoli, Claudia; Wu, Jie; Yau, Shing-Tung; Wu, Rongling
• 署名单位: Chinese Academy of Fishery Sciences; Fishery Engineering Research Institute, CAFS; Beijing Forestry University; Tsinghua University; Nankai University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; Creighton University; Tsinghua University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-8575
• DOI: 10.1073/pnas.2412220121
• 发表日期: 2024-10-01
• 关键词: dynamics; physics

摘要

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.