Gene expression profiling is increasingly being used to study complex disease processes, with a focus toward generating new hypotheses and identifying novel therapeutic approaches. This method requires not only the ability to assign expression data to the correct cell type, but also the aptitude to interpret the subsequent deluge of gene expression patterns. Single-cell gene expression analysis is currently used to generate data within the fundamental unit, the single cell, thereby freeing the analysis from assumptions or questions regarding cell population homogeneity, whether cell-type or temporal. Single-cell expression profiling also offers a highly parallel view of the workings of a gene regulatory network at one specific point in time, and will hopefully provide insights that could lead to an improved ability to interpret gene expression patterns.