Complex Biological Systems and Mathematical Biology
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Biology".
Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 16973
Special Issue Editors
Interests: mathematic biology; infectious disease dynamics; nonlinear dynamics; big data analysis in medicine and public health
Special Issue Information
Dear Colleagues,
The importance of mathematical modelling approaches for understanding and controlling major diseases, including communicable and non-communicable diseases, is widely accepted. Mathematical models play an increasingly important role in the prediction and early warning of emerging infectious disease outbreaks or developments in non-communicable diseases, optimizing non-pharmaceutical interventions, therapeutic strategies, and so on. We believe that modelers can make substantial contributions to innovating modelling and analysis methods, providing a better understanding of the dynamic mechanisms of complex biological systems, and helping to solve the current major issues in biomedicine. For this reason, we have initiated a Special Issue focusing on new developments in the fast-growing field of mathematical models of complex biological systems. Potential topics include—but are not limited to—the following:
- Mathematical modelling and analysis to understand complex biological systems;
- Dynamic mechanism of complex biological systems;
- Optimization and control for complex biological systems;
- Data-driven modeling of complex biological systems;
- Machine learning approaches to biological systems;
- Advanced computational methods and data science for biology and biomedicine, etc.
Dr. Biao Tang
Dr. Xia Wang
Guest Editors
Manuscript Submission Information
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Keywords
- infectious disease modelling
- epidemiological dynamics
- piecewise dynamic systems
- optimal control in COVID-19
- human behaviours evolution dynamics
- data-driven modelling
- modelling non-communicable diseases
- machine learning approaches
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