Presentation Title

A Novel Approach to Metabolic Pathway Modeling

Advisor Information

Paul Davis

Location

UNO Criss Library, Room 231

Presentation Type

Oral Presentation

Start Date

4-3-2016 10:15 AM

End Date

4-3-2016 10:30 AM

Abstract

Computational methods of metabolic pathway modeling allow a better understanding of health, disease, and basic biological principles of regulation and metabolism, yet, it is a laborious process. Using the queueing theory, an approach commonly employed to evaluate telecommunication networks, significantly reduces the computational power required to generate simulated results, while simultaneously reducing expansion of errors inherent to classical approaches. The novel approach to calculating biomolecular interactions, requires less computational effort and yields results at least as predictive of molecular outcomes as currently employed methods. A non-trivial amount of cells were simulated and the average concentrations per cell were graphed as a function of time. Variations of 10% of glucose levels are randomly computed for every simulated second. Our data shows that we are able to simulate the glycolysis pathway in human cancer cells in accord with experimentally derived data 30 minutes post-stimulation.

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Mar 4th, 10:15 AM Mar 4th, 10:30 AM

A Novel Approach to Metabolic Pathway Modeling

UNO Criss Library, Room 231

Computational methods of metabolic pathway modeling allow a better understanding of health, disease, and basic biological principles of regulation and metabolism, yet, it is a laborious process. Using the queueing theory, an approach commonly employed to evaluate telecommunication networks, significantly reduces the computational power required to generate simulated results, while simultaneously reducing expansion of errors inherent to classical approaches. The novel approach to calculating biomolecular interactions, requires less computational effort and yields results at least as predictive of molecular outcomes as currently employed methods. A non-trivial amount of cells were simulated and the average concentrations per cell were graphed as a function of time. Variations of 10% of glucose levels are randomly computed for every simulated second. Our data shows that we are able to simulate the glycolysis pathway in human cancer cells in accord with experimentally derived data 30 minutes post-stimulation.