Date of Award
Thesis open access
Modeling sophisticated biological systems in a way that makes them more apprehensible, without losing comprehension or robustness, is challenging task. The flux balance analysis FBA) model describes metabolic networks of single-celled organisms with the goal of simulating their steady-state behavior. FBA simulations yield reliable and biologically relevant growth rate values, but do not simulate intra-cellular behavior well.
Solutions to the FBA model are often degenerate and non-unique. Ideally, the model should simulate metabolic activity in exactly one way under any given circumstances--the way the real organism's metabolism behaves. The ultimate goal of this project is to better understand the FBA model in order to improve it, so that this ideal may be more achievable.
An overview of biological networks, metabolism, and FBA is given to familiarize the reader. Dominance, the amount that a reaction dominates consumption or production of its reactants and products over other reactions, is used to define a partition of the metabolism that groups reactions with similar properties. The term minimal environment is defined to describe a set of metabolic resources that are limiting for a certain growth rate, and an algorithm is developed for finding the minimal environment of a metabolic network.
Dominance is found to be an indicator for certain regions of the network that are cyclic, and thus problematic. An algorithm is developed for finding cycles in a graph, which is then applied to the metabolic network. The complexity of this algorithm when applied to E. coli makes it too computationally diffcult to be used, but the algorithm is useful in other respects.
Nunamaker, Tim, "Cycles in Metabolic Networks" (2008). Computer Science Honors Theses. 25.