Gene expression profiling will revolutionize biology. That much is universally agreed. But it’s harder than it looks. In part, the reasons can be technical—substandard arrays, low signal: noise ratios for rare transcripts, variable backgrounds, cross-hybridizations, the difficulty of processing clinical materials, and so forth. But more often the reasons relate to analysis and interpretation of the data. Inevitably, more time and energy are spent after the experiments are finished than before. We can identify a number of necessary tasks in the analysis of gene expression data, as summarized in Table 1. In the following capsule descriptions, we will focus for concreteness on the two-color fluorescence technologies (1), but analogous steps are pertinent to one-color fluorescence and radioactive detection methods as well. With apologies to the many scientists who have been innovative in this field, we intend, in this short summary, to indicate requirements and options rather than to give a comprehensive review or to apportion credit for the various contributions. The examples will focus primarily on studies from our laboratory.