The physiological functions of a tissue in the body are carried out by its complement of expressed genes. Genes that execute a particular function should be more specifically expressed in tissues that perform the function. Given this premise, we mined public microarray expression data to build a database of genes ranked by their specificity of expression in multiple organs. The database permitted the accurate identification of genes and functions known to be specific to individual organs. Next, we used the database to predict transcriptional regulators of brown adipose tissue (BAT) and validated two candidate genes. Based upon hypotheses regarding pathways shared between combinations of BAT or white adipose tissue (WAT) and other organs, we identified genes that met threshold criteria for specific or counterspecific expression in each tissue. By contrasting WAT to the heart and BAT, the two most mitochondria-rich tissues in the body, we discovered a novel function for the transcription factor ESRRG in the induction of BAT genes in white adipocytes. Because the heart and other estrogen-related receptor gamma (ESRRG)-rich tissues do not express BAT markers, we hypothesized that an adipocyte co-regulator acts with ESRRG. By comparing WAT and BAT to the heart, brain, kidney and skeletal muscle, we discovered that an isoform of the transcription factor sterol regulatory element binding transcription factor 1 (SREBF1) induces BAT markers in C2C12 myocytes in the presence of ESRRG. The results demonstrate a straightforward bioinformatic strategy to associate genes with functions. The database upon which the strategy is based is provided so that investigators can perform their own screens.