Cellular functions are controlled by genetic regulatory networks called gene circuits. Recently, there has been much interest in how gene circuits deal with or even exploit stochastic fluctuations in molecular species within the cellular environment. Through a coupling of analysis and simulation with experimentation, this dissertation work furthers the understanding of gene circuit noise behavior and makes significant contributions to the analytical and experimental tools that are currently available for the study and design of natural and synthetic gene circuits. In this study, models are developed for unregulated and autoregulated gene circuits. Results from the analysis are compared to computer simulations and experimental results. Exact stochastic simulations show that the derived analytical expressions are valid even for populations as low as 10 molecules, despite linear approximations made by the analysis. The experimental portion of this work presents a novel method for acquiring in vivo measurements of real-time gene expression. The techniques developed here are used to report the very first measurements of frequency content in gene circuit noise and verify theoretical predictions that negatively autoregulated gene circuits shift their noise spectra up to higher frequency. Through measured shifts in noise spectra, these frequency measurements can also reveal subtle and condition-dependent regulatory pathways. Measured noise spectra may also permit in vivo estimation of gene circuit kinetic rate parameters