Although both genomic sequencing and expression analysis are becoming indispensable for biological research, methods that can effectively survey large public gene expression repositories remain to be established. In this study, we developed an approach for the retrieval of tissue-specific expression information for certain genes from public databases; our approach was based on performance of a basic local alignment search tool search against probes on DNA microarray chips. To test the effectiveness of this approach, we examined the expression of human odorant receptors in non-olfactory tissues, as recent studies showed that such non-olfactory odorant receptors have physiological and pathophysiological significance. When we screened a large expression data set using this approach, we were able to effectively identify candidate odorant receptors in non-olfactory tissues and confirmed their expression by reverse transcription-polymerase chain reaction. Using receiver-operating characteristic curve analysis, the sensitivity and the specificity of this approach were 60 and 68%, respectively, indicating that the use of this technique would efficiently identify the previously unidentified expression of odorant receptors in non-olfactory tissues. Taken together, the in silico approach, as shown in the present study, would facilitate to elucidate the function of genes of interest.