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A mechanistic understanding of gene regulatory network dynamics requires quantitative single-cell data of multiple network components in response to well-defined perturbations. Recent advances in the development of fluorescent biomarkers for proteins, detection of RNA and interactions, microfluidic technology, and high-resolution imaging have set the stage for a host of new studies that elucidate the important roles of stochasticity and cell–cell variability in response to external perturbations. In this review, we briefly describe methods for high-resolution visualization and the control of gene expression, along with application of these novel methods to recent studies involving gene networks. [ABSTRACT FROM AUTHOR]