About this Research Topic
A very hotly debated topic in past years is mathematics in healthcare and the modeling of biomedical applications such as tumour growth, tissue regeneration, electrophysiological behavior of the heart or the brain, and many more. Mathematical and computational modeling became an essential component in numerous interdisciplinary and multidisciplinary research projects and contributes significantly to a better understanding of real-world phenomena. In this line of research, there are plenty of important examples of mathematical and numerical approaches which are used for drug (safety) testing or drug development and are becoming more and more relevant these days. As a further example, computer modeling of complex dynamic processes like bone healing gives new insights into how such complex biological processes are working and helps to make better predictions.
One reason for this development is that we have great opportunities nowadays to derive very detailed but also complex models from experimental data. In addition, the development in computational methods opens new challenges and prospects for a systematical investigation of issues from life science like cardiovascular and neurological diseases and disorders. In this sense, this Research Topic focuses on advanced methods in mathematical and computational modeling of biomedical phenomena using (experimental) data, e.g., from biology, physics and/or medicine, their analysis and numerical simulations that contribute to a significantly improved comprehension of these phenomena. It aims for 1) new and innovative modeling approaches using, for example, differential equations or networks describing the behavior of single cells, cell groups, tissue or organs. 2) The analysis of the dynamics and behavior of certain biomedical models improving the state-of-art understanding of certain phenomena like disorders and diseases. 3) Improved numerical methods to simulate and/or analyze complex biomedical models.
Manuscripts are welcome which are dedicated to the development of theoretical, numerical and/or experimental studies of biomedical problems using mathematical tools and advanced mathematical approaches to tackle recent challenges in biomedicine.
Topics of interest include, but are not limited to, the following list:
- Deterministic and stochastic problems
- Biomedical applications
- Biophysical modeling
- Data-driven modeling
- Applied analysis
- Bifurcation theory and multiple time scales
- Mathematical and computational neurosciences and cardiology
- Synchronisation
- Agent-based modeling
- Self-organising pattern
One reason for this development is that we have great opportunities nowadays to derive very detailed but also complex models from experimental data. In addition, the development in computational methods opens new challenges and prospects for a systematical investigation of issues from life science like cardiovascular and neurological diseases and disorders. In this sense, this Research Topic focuses on advanced methods in mathematical and computational modeling of biomedical phenomena using (experimental) data, e.g., from biology, physics and/or medicine, their analysis and numerical simulations that contribute to a significantly improved comprehension of these phenomena. It aims for 1) new and innovative modeling approaches using, for example, differential equations or networks describing the behavior of single cells, cell groups, tissue or organs. 2) The analysis of the dynamics and behavior of certain biomedical models improving the state-of-art understanding of certain phenomena like disorders and diseases. 3) Improved numerical methods to simulate and/or analyze complex biomedical models.
Manuscripts are welcome which are dedicated to the development of theoretical, numerical and/or experimental studies of biomedical problems using mathematical tools and advanced mathematical approaches to tackle recent challenges in biomedicine.
Topics of interest include, but are not limited to, the following list:
- Deterministic and stochastic problems
- Biomedical applications
- Biophysical modeling
- Data-driven modeling
- Applied analysis
- Bifurcation theory and multiple time scales
- Mathematical and computational neurosciences and cardiology
- Synchronisation
- Agent-based modeling
- Self-organising pattern
Keywords: mathematical and computational modeling, biomedical applications, applied analysis, complex dynamic processes, computational medicine, differential equations, network
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.
