The ability to self-regulate in feedback is what allows cells to operate robustly despite the uncertainties of both a changing external environment and their own internal biochemistry. While feedbacks underlie many dramatic cellular behaviors including cell fate decisions and chemotaxis, the vast majority of feedback is responsible for more subtle changes such as quantitatively shaping the time scales and strength of a signaling response. In these cases, the traditional genetic perturbations such as gene knockout or overexpression that are commonly used to identify feedback regulators are ill-suited for investigating their function, in part because feedback is inherently dynamic. The aforementioned static perturbations cannot test hypothesis with respect to when and how much feedback is needed for normal cellular function. This is further compounded by the system level nature of feedback as these genetic perturbations to a feedback regulator can be obscured by compensatory changes occurring in the system the feedback regulates.

In this work, we address these issues by developing a new method, closed loop optogenetic control (CLOC), for systematically determining the temporal requirements of feedback regulators of a signaling pathway. This method, which uses control theory to extend the classical genetic compensation framework to the study of feedback, relies on the ability to precisely and in real time control the activity of a feedback regulator. This is accomplished through the use of a custom built hardware and software infrastructure that allows for \textit{in silico} control of an optogenetically activated version of the feedback regulator. The platform monitors in real time the output of a pathway deleted for a feedback regulator and automatically calculates and delivers the appropriate light input needed activate the optogenetic feedback regulator and compensate for the effects of the feedback deletion. The time varying optogenetic input needed to rescue wild type signaling dynamics serves as proxy for defining the temporal requirements of a feedback regulator in the context of native pathway signaling. In chapter 2, previous work related to in silico control of intracellular processes is reviewed. In chapter 3, I introduce the idea of studying signaling pathways using non-traditional, quantitative genetic perturbations by investigating the effect of graded expression of pathway regulators on yeast mating pathway signaling. In chapter 4 I develop CLOC as a method and use it to study three negative feedback regulators of the yeast pheromone mating pathway: SST2, MSG5, and GPA1. Surprisingly, CLOC revealed distinct dynamic requirements for the expression of each of the three feedback regulators.