Even genetically identical cells in identical environments exhibit wildly different phenotypical behaviors due to cellular fluctuations known as gene expression "noise". Previously, such noise was considered a nuisance that compromised cellular responses, complicated modeling, and made predictive understanding all but impossible. Many studies focused on how cellular processes remove or exploit noise to a cell's advantage. However, different cellular mechanisms affect these cellular fluctuations in different ways, and it is now clear that these fluctuations contain valuable information about underlying cellular mechanisms. Finding and exploiting this information requires a strong integration of single-cell/single-molecule measurements with discrete stochastic analyses. My focus is to utilize this information to gain predictive understanding of new biological phenomena. Along these lines, we have studied natural and synthetic transcriptional regulation pathways in bacteria, yeast and mammalian cells.