Manuscript Topics

Nonlinear dynamics and dynamical systems approaches and methodologies have been increasingly recognized as powerful methods for understanding and addressing complex biomedical research problems as well as decision making. In recent years, there has been significant progress in the development of new methods and concepts for the nonlinear dynamical modeling of processes in complex biomedical systems (such as cardiovascular dynamics, tumor dynamics and cell mobility, pharmacokinetic and pharmacodynamic, immune dynamics, dynamics in brain, physiological dynamic signals, and so on). These progresses have significantly improved the understanding of mechanisms of these processes and allowed the deepening of analysis of the information contained therein. However, there are many interesting theoretical aspects of biomedical science that are not fully explored and exploited.

This exciting interdisciplinary and transdisciplinary field interests an increasing number of mathematicians and biologists across the world as well as physical chemists and engineers, which are motivated by the combination of fundamental approach with practical applications of current interest in the broad fields of mathematical biology and dynamics of the underlying physical and chemical processes.

This field also has a key role in contributing to the predictive mathematical modeling, by serving, e.g., as a bridge between the large-scale biomedical data (clinical, imaging, bio sample and experimental), the biologist, and the clinician. In this way, it is used, among others, to bridge gaps in sparse data, to make predictions about how systems will respond to change and uncertainty, and to increase the reliability of diagnosis and prediction of the disease progression and response to therapy on a specific patient (optimizing personalized medicine).

To effectively understand and study (qualitatively and quantitatively) dynamics associated with biomedical phenomena requires drawing upon a variety of mathematical concepts, procedures and tools from nonlinear dynamical systems and computational fields to multi-scale agent-based models to robust control theory and chaotic dynamical systems, with results obtained through mathematical analysis or computational simulations.

In this context, we invite researchers to contribute to original research articles that fall within the broad category of nonlinear dynamics on biomedical systems.

Contributions should use theoretical approaches to address questions of biomedical interest from a dynamical systems point of view. A variety of mathematical approaches and frameworks are welcome, provided that the deeper understanding of biomedical system dynamics' behavior is the primary goal of the work. Papers in which theoretical analysis are substantiated by numerical simulations are encouraged.

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