
The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here, we develop a framework to probe interactions among diverse systems, and we identify a physiologic network. We find that each physiologic state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiologic states the network undergoes topological transitions associated with fast reorganization of physiologic interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.
12 pages, 9 figures
Adult, Male, Statistical Mechanics (cond-mat.stat-mech), Molecular Networks (q-bio.MN), FOS: Physical sciences, Models, Biological, Young Adult, Physics - Data Analysis, Statistics and Probability, FOS: Biological sciences, Humans, Quantitative Biology - Molecular Networks, Female, Sleep Stages, Condensed Matter - Statistical Mechanics, Physiological Phenomena, Data Analysis, Statistics and Probability (physics.data-an), Signal Transduction
Adult, Male, Statistical Mechanics (cond-mat.stat-mech), Molecular Networks (q-bio.MN), FOS: Physical sciences, Models, Biological, Young Adult, Physics - Data Analysis, Statistics and Probability, FOS: Biological sciences, Humans, Quantitative Biology - Molecular Networks, Female, Sleep Stages, Condensed Matter - Statistical Mechanics, Physiological Phenomena, Data Analysis, Statistics and Probability (physics.data-an), Signal Transduction
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 641 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
