The promise of gene expression profiling using microarray technology has inspired much new hope for finding genes involved in complications resulting from burn injury. It has become clear that complications resulting from burn injury involve collective action of many genes. Therefore, genetic dissection of burn injury should be carried out in a global context. Gene expression microarrays (GEMA) provide such global information of transcription activities of essentially all genes simultaneously. It is hoped that this promising technology can be applied to samples drawn from large-scale, well-defined clinical studies and help us untangle the web of pathways leading to complications resulting from burn injury and to the development of more effective therapies for treating burn injury. However, the extremely high dimensionality and noise inherent in GEMA data pose great challenges to identifying molecular signatures involved in burn injury. In this article, we discuss the technical challenges associated with experimental design, data analysis, and modeling gene regulatory networks. We note that while it is too early to tell how much of the enormous potential of GEMA will be realized, its success will likely depend most critically on careful experimental designs and the ability of bioinformatics to rise to the challenge of mining high dimensional GEMA data and correlating it with clinical information.