Complex Dynamics in Biological Systems: A Bifurcation Theory Approach

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Many problems arising in biological systems can be modelled by nonlinear ordinary differential equations (ODE), which can describe complex phenomena such as population growth, spread of diseases, recurrent infection, etc. Such dynamical processes often exhibit qualitative changes, called bifurcations like population explosions and disease outbreaks. Bifurcation theory is a powerful tool in studying bifurcation phenomena as it explains how small changes in the system parameters can lead to these qualitative changes. The methods of bifurcation theory enable us to identify the parameter values where bifurcations occur, and to predict the qualitative changes in behaviour of the system near the bifurcation points. Among various bifurcations, Hopf bifurcation and Bogdanov-Takens (B-T) bifurcation are two main bifurcations, leading to a special type of  periodic solutions - limit cycles, which is a self-sustained oscillation and appears in almost all physical systems. In order to analyze these bifurcations, centre manifold theory and normal form theory need be used to greatly simplify system equations by extracting the "key'' information (or terms) to form a simple system, while keeping the qualitative behaviour of the system unchanged near bifurcation points. Further, the simplest normal form (SNF) theory and parametric simplest normal (PNSF) theory, developed two decades ago were eventually applied to solve the B-T bifurcation of real world systems. Another interesting phenomenon often observed in physical and biological systems is the "slow-fast" motion such as recurrent behaviour in diseases. However, such slow-fast motions cannot be identified or analyzed by the well-known geometric singular perturbation theory (GSPT), which has been widely applied to study slow-fast motions in singular perturbed dynamical systems. A new method based on dynamical systems theory has been developed, which contains four conditions, to easily identify such slow-fast motions. Moreover, compared to the GSPT, our novel, simple approach can be easily applied to study such slow-fast motions in higher dimensional dynamical systems. This proposed research program has three objectives. The first one is to develop the SNF and PSNF theories and efficient computation methods/algorithms for general n-dimensional dynamical systems described by ODEs. The second one is to develop a rigorous mathematical theory for the dynamical system approach to identify the special oscillating slow-fast motions. The third one is to apply the new theory and methods to investigate more biological systems such as predator-prey systems and HIV models. These applications are not only significant for increasing scientific understanding, but progress may yield practical, clinical benefits.