We are approaching the “post-genomic era” when clinicians will be able to use microarrays during early clinical trials to confirm the mechanisms of action of drugs, and to assess drug sensitivity and toxicity. Coupled with more conventional biochemical analysis such as im­munohistochemistry (IHC) and enzyme-linked immuno­sorbent assay (ELISA), microarrays will soon be used for diagnostic and prognostic purposes. As nucleic acid arrays begin to penetrate the research community, technologists are already entertaining visions of protein arrays, antibody arrays and cell arrays, as well as non-array-based global readouts. RNA-expression analysis represents only one parameter by which cells or tissues may be characterized. Depending on the experiment, epidemiological or molecular pathological data, genomic changes (gains or losses) or sensitivity to drugs, are additional parameters that influence the interpretation of microarray data. The ability to combine RNA and protein expression data to profile both transcriptional and post-transcriptional changes in cells and tissues arises. The number of proteins that can be profiled at this stage is still substantially less than the number of genes. It is difficult to identify proteins that are differentially expressed, but there are techniques for rapid and reproducible protein separation and identification. This makes proteomics a highly desirable adjunct to microarray RNA expression analysis [61].