The DNA microarray is a powerful, high throughput technique for assessing gene expression on a system-wide genomic scale. It has great potential in pain research for determining the network of gene regulation in different pain conditions, and also for producing detailed gene expression maps in anatomical areas that process nociceptive stimuli. However, for the potential of this high throughput technology to be realised in pain research, microarrays need to be combined with other technologies. Laser capture microdissection is capable of isolating small populations of homogenous cells, allowing distinct areas involved in nociceptive processing to be examined. In combination with sophisticated PCR-based amplification protocols this technique provides sufficient amounts of messenger RNA (mRNA) for application to microarrays. Aside from the technological issues, a difficult task in any microarray study is the analysis of the resulting enormous data set to reveal the key genes, whose regulation is central to the phenotypic changes observed. For this to be achieved, the methods of data analysis, pattern searching and feature recognition, and bioinformatics have to be properly deployed all within the context of an appropriate statistical design. These issues are especially relevant to pain research where interindividual and interpopulation variation is likely to be high, and where polymorphisms can greatly affect nociceptive sensitivity and susceptibility to pain conditions. Methods for assessing the function of new candidate genes identified in microarray screening experiments are also discussed.