Major Department

Biomedical Engineering


College of Engineering


BSE (Bachelor of Science in Engineering)

Session and Year of Graduation

Spring 2018

Honors Major Advisor

David G. Wilder

Thesis Mentor

Michael A. Mackey


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.


Biochemical Modeling, Mathematical Modeling, Systems Biology, Biochemistry

Total Pages

23 pages


Copyright © 2018 Ethan Stancliffe