Experimental design and mathematical modeling in ODE-based systems biology
Jeong, Jenny E.
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The ODE based modeling is usually used to describe the biological processes and it contains many unknown model parameters. These parameters should be estimated based on the experimentally observed data. However, the amount of experimental data is almost always limited compared to the complexity of the model, and this gap makes parameter estimation more challenging. To improve parameter estimation, experimental design and model reduction methods are usually used. In this thesis, the combination of these two distinct methods has been introduced as a new potential approach for improving parameter estimation. Furthermore, a new approach quantifying the relative importance of each data point and giving a different weight to each data according to the quantified importance has been demonstrated. This approach can find parameters which can fit the dynamically changing region rather than the steady state. Lastly, as an application, modeling the passive microfluidic cell sorting device has been shown.