About this Research Topic
Frontiers in Network Physiology is delighted to present the article collection “Information Theory in Network Physiology: State of the Art and New Perspectives”, part of a series of Research Topics reviewing the current status of the field.
The collection will publish high-quality scholarly review papers, methods and opinion articles on key topics in Information Theory. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. We anticipate the research presented will promote discussion and stimulate understanding and future investigation in the Network Physiology community as well as in the broader field of Information Theory applied to the analysis of dynamic systems in biology, physiology and neuroscience.
The collection “Information Theory in Network Physiology: State of the Art and New Perspectives” welcomes full-length or mini review articles, perspectives and opinion pieces across the full Information Theory section scope. New articles will be added to this collection as they are published.
Potential topics of interest include but are not limited to the following:
• Model-based and model-free estimation of system complexity
• Univariate, bivariate and multivariate measures applied to dynamic networks
• Methods for the analysis of information dynamics in network systems
• High-order interactions: methodologies and applications
• Information storage and information transfer in physiological systems
• Granger causality analysis
• Information-theoretic analysis and spectral analysis of time series
• Statistically validated networks
• Graph theory applied to Network Physiology
• State of art and future directions in the application of information theory to brain, physiological and biological networks
The collection will publish high-quality scholarly review papers, methods and opinion articles on key topics in Information Theory. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. We anticipate the research presented will promote discussion and stimulate understanding and future investigation in the Network Physiology community as well as in the broader field of Information Theory applied to the analysis of dynamic systems in biology, physiology and neuroscience.
The collection “Information Theory in Network Physiology: State of the Art and New Perspectives” welcomes full-length or mini review articles, perspectives and opinion pieces across the full Information Theory section scope. New articles will be added to this collection as they are published.
Potential topics of interest include but are not limited to the following:
• Model-based and model-free estimation of system complexity
• Univariate, bivariate and multivariate measures applied to dynamic networks
• Methods for the analysis of information dynamics in network systems
• High-order interactions: methodologies and applications
• Information storage and information transfer in physiological systems
• Granger causality analysis
• Information-theoretic analysis and spectral analysis of time series
• Statistically validated networks
• Graph theory applied to Network Physiology
• State of art and future directions in the application of information theory to brain, physiological and biological networks
Keywords: Information Theory, network physiology, dynamic systems, biology, neuroscience, physiological systems, complexity, models, Granger Causality
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
