Stochastic Models for mRNA Transcription (thesis)

Abstract

Gene regulation is essential for the diversity and maintenance of life. The first step in protein production, and therefore the first step in gene regulation activities, is transcription. This thesis will outline and analyze three different stochastic models of mRNA transcription. Stochastic models capture the randomness activity on a microscopic level within cells to then predict macroscopic behavior. The stochastic models presented here begin with a one-state model and increase in complexity to three state and multi-state, models. Future goals include increasing model complexity to more accurately capture biological phenomena, and incorporating real biological rates of mRNA birth and death as well as rates of gene activation and inactivation.