As the genomic regions containing loci predisposing to obesity-related traits are mapped in human population screens and mouse genetic studies, identification of susceptibility genes will be increasingly facilitated by bioinformatic methods. We hypothesized that candidate genes can be prioritized by their expression levels in tissues of central importance in obesity. Our objective was to develop a combined bioinformatics and molecular paradigm to identify novel genes as candidates for murine or human obesity genetic modifiers, based on their differential expression patterns in the hypothalamus compared to other murine tissues. We used bioinformatics tools to search publicly available gene expression databases using criteria designed to identify novel genes differentially expressed in the hypothalamus. We used RNA methods to determine their expression sites and levels of expression in the hypothalamus of the murine brain. We identified the chromosomal location of the novel genes in mice and in humans, and compared these locations to those of genetic loci predisposing to obesity-related traits. We developed a search strategy that correctly identified a set of genes known to be important in hypothalamic function, as well as a candidate gene for Prader-Willi syndrome that was not previously identified as differentially expressed in the hypothalamus. Using this same strategy, we identified and characterized a set of eleven genes not previously known to be differentially expressed in the murine hypothalamus. Our results demonstrate the feasibility of combined bioinformatics and molecular approaches to the identification of genes that are candidates for obesity-related disorders in humans and in mice.