Network Physiology and Complex Systems: Reviews and Data Across Biological Scales

Physiological and cellular systems generate complex, interdependent, and often nonlinear data, from cardiovascular and autonomic signals to cellular signaling and metabolomic profiles. Understanding this complexity relies on network physiology and nonlinear dynamics, increasingly supported by computational and machine learning approaches for identifying structure, causality, and dysfunction across biological scales.This Research Topic welcomes review articles and data-focused contributions, including FAIR2 Data Articles, that examine complex physiological and cellular systems using these approaches. This includes exploring how organizational and emergent behaviors arise from the interconnection of physiological or biological agents, with attention to ethical considerations where AI and machine learning are applied to physiological or cellular data. Relevant systems include, but are not limited to, brain–heart interactions, autonomic control, cardiovascular and cerebrovascular regulation, respiratory and renal networks, and neuro-autonomic and neuro-immune coupling. This also extends to cellular-level processes such as calcium signaling and cell fate decisions, including applications in oncology and disease diagnostics.We invite review articles and curated datasets covering methodology, application domains, and cross-disciplinary perspectives bridging physics-based and biology-based approaches to complex systems. Topic editors: Elbert E N Macau, Rawad Hodeify, Vlasta Bari Source: https://www.frontiersin.org/research-topics/83473/network-physiology-and-complex-systems-reviews-and-data-across-biological-scales