Date of Award

2011

Document Type

Honors Thesis (Open Access)

Department

Colby College. Computer Science Dept.

Advisor(s)

Stephanie R. Taylor

Second Advisor

Bruce A. Maxwell

Abstract

Circadian rhythms are found in plants, animals, fungi, and bacteria and are responsible for the regulation of many biological, physiological, behavioral, and metabolic activities. In mammals, the “master” clock is embedded in the suprachiasmatic nuclei (SCN) of the anterior hypothalamus. It is composed of thousands of cells signaling each other to synchronize and produce a unified rhythm. It is hypothesized that this communication enables the clock to rescue rhythms in gene knockout experiments that destroy oscillations at the single cell level. Henry Mirsky developed a model of this gene regulatory network within a single cell in 2009, but the published model is unable to accurately predict some knockout phenotypes in tissue. We determined that binary ‘arrhythmic’ and ‘rhythmic’ classifications were unsuitable for describing cellular behavior, so we utilized a novel ‘damped’ classification to describe cellular phenotype. We then used a genetic algorithm optimization technique to fit the model’s parameters to better mimic damped Cry1 single-cell knockout behavior. This optimization produced a parameter set that is able to correctly predict all single-cell knockout phenotypes as well as accurately predict the oscillatory phenotypes for two additional SCN tissue knockouts not previously demonstrated. The rescue of oscillations was confirmed by simulating SCN tissue—a process that involves reproduction of intercellular signaling and normal variation of unique cellular parameter sets. Further work seeks to explain the causes for the ability of this new parameter set to rescue oscillations in tissue simulations where the published parameter set was unsuccessful.

Keywords

Circadian rhythms

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