We present a powerful new approach for comparative expression analysis combining two data-mining strategies followed by experimental verification.The endothelium plays a pivotal role in many physiological and pathological processes and is known to be an exceptionally active transcriptional site. To advance our understanding of endothelial cell biology and to elucidate potential pharmaceutical targets, we have developed a new database screening approach to permit identification of new endothelial-cell-specific genes. We screened the UniGene index using high-stringency BLAST against a pool of endothelial and a pool of non-endothelial expressed sequence tags constructed from cell-type-specific db expressed sequence tag libraries. UniGene clusters with matches in the endothelial pool and no matches in the non-endothelial pool were selected. We then combined this approach with Serial Analysis of Gene Expression–library subtraction and the polymerase chain reaction with reverse transcription to further examine clusters of interest. We identified and labeled four new genes: those coding for endothelial-cell-specific molecules (ECSM) 1–3 and magic roundabout (similar to the axon guidance protein roundabout).