Understanding many cellular processes demands an integrative approach, considering systems of interacting biomolecules, rather than focusing on individual genes or proteins. For example, cell-cycle checkpoints are bistable, in that the cell either divides or it doesn't, with no intermediate outcome possible. This bistability arises not from a particular gene, but rather through the nonlinear interactions of multiple genes in a network. Depending on the problem, dechiphering such complex nonlinear systems demands assays that measure many cellular components simultaneously or assays that track individual cells rather than populations. Understanding the resulting data is often greatly aided by computational approaches, either to processed the large data sets, or to develop computational models that reproduce particular cellular behaviors.