Drug discovery rests on an ability to identify effects of compounds on their intended targets, but it also requires an ability to monitor other activities of compounds that are unintended. Over the past several years, individuals have recognized that it is possible to use transcript arrays to follow the levels of expression for many of the genes in cells. The emphasis has been placed on monitoring transcriptional units to understand the transcriptome. This is quite helpful in understanding biology, but does not provide information regarding the activity or function of various proteins in the cell. This lecture will focus on the ability of expression profiling to follow protein function. The emphasis here is on using matrix approaches and pattern recognition to move beyond the analysis of transcript levels to being able to follow the function of intended and unintended targets in the cell. The strategy that we have employed involves building up large, coherent sets of data and developing algorithms and other tools by which to successfully compare new profiles with those existing in libraries of profiles.