The complexity of biochemical networks necessitates the use of computational and mathematical frameworks to accurately characterize and study these systems. However, modern frameworks developed for this task have inadequacies that limit their accuracy or scalability. In this report, a mathematical model of the canonical enzyme substrate binding network is developed, and, using estimated true and maximal reaction rates, a methodology utilizing principles of flux balance analysis is developed to deduce the individual reaction rate constants in the network. It is then shown that these two reaction rates are not sufficient to unambiguously define a mass action kinetic model of this network. Nevertheless, the methodology developed greatly reduces the degrees of freedom of the system, and, as a result, the solution space of the network can be examined computationally and analytically revealing several non-intuitive sensitivities.
Thesis
Mass Action Modeling of Catalysis Through Reaction Flux Estimation
University of Iowa
Bachelor of Science in Engineering (BSE) , University of Iowa
Spring 2018
Abstract
Details
- Title: Subtitle
- Mass Action Modeling of Catalysis Through Reaction Flux Estimation
- Creators
- Ethan Stancliffe - University of Iowa
- Contributors
- David G Wilder (Advisor)Michael A Mackey (Mentor) - University of Iowa, Roy J. Carver Department of Biomedical Engineering
- Resource Type
- Thesis
- Project Type
- Honors Thesis
- Degree Awarded
- Bachelor of Science in Engineering (BSE) , University of Iowa
- Degree in
- Biomedical Engineering
- Date degree season
- Spring 2018
- Publisher
- University of Iowa
- Number of pages
- 23 pages
- Copyright
- Copyright © 2018 Ethan Stancliffe
- Language
- English
- Academic Unit
- Engineering Honors Theses; Honors Program
- Record Identifier
- 9984109975802771
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