Mathematical Modeling and Optimal Experimental Design in Systems Biology

Date of Award

2011

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

Yildirim, Necmettin

Keywords

Systems Biology, Feedback, Enzyme Kinetics

Area of Concentration

Applied Mathematics

Abstract

Mathematical modeling can sometimes be used to better understand how complex reaction networks behave in biological systems. However, a problem often encountered is the existence of multiple models developed from different interaction mechanisms that fit experimental data equally well. An optimal experiment such that these mechanisms can be discriminated is critical in order to determine the correct mechanism. Mathematical models can be used in designing these experiments that will invalidate the incorrect mechanisms and reduce the time and cost of using multiple, non-optimal experiments to achieve the same goal. In this study a discrimination method of initial condition optimization to maximize the differences between model outputs is described and detailed. Then it is applied to two inhibition models in enzyme kinetics to show how the method works. It is then used on a hypothetical system with two different types of positive feedback loops to develop the complete experimental protocol for designing an optimized experiment directly from experimental data. This method shows that only a total of two time series data sets are needed to differentiate two competing models.

Rights

This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.

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