For many years, biological scientists have sought to decipher cellular function by quantifying the degrees of protein and mRNA expression within populations of their cells of interest. Classically, these measurements required combining many cells into a single sample and rupturing their membranes, thus exposing pooled quantities of the target molecule for detection. One limitation of these techniques is the reliance on average measurements: it is impossible to distinguish a uniform population of cells expressing intermediate quantities of a molecule from a population composed of separate low and high expressers. The distinction has proven to be important, particularly in the context of drug targeting of cancer cells; prescribing a dose to hit the "average" cell may completely miss the more aggressive "one percent." The advent of single-cell measurement technology such as flow cytometry and RNA FISH has made it possible to capture not only a population's average levels of a molecule, but also the distribution of the molecule's expression within the population. As a result, researchers are increasingly investigating the sources and significance of variability within populations that were previously assumed to be identical.