Abstract
We describe TissueInfo, a knowledge-based method for the high-throughput identification of tissue expression profiles and tissue specificity. TissueInfo defines a set of tissue information calculations that can be computed for large numbers of genes, expressed sequence tags (ESTs) or proteins. Tissue information records that result from the TissueInfo calculations are used to generate tables suitable for data mining and for the selection of genes according to a given expression profile or specificity. When benchmarked against a test set of 116 proteins and literature information, TissueInfo was found to be accurate for 69% of identified tissue specificities and for 80% of expression profiles. The accuracy of the identifications can be increased if query sequences for which little information is available from dbEST are ignored. Thus, with 80% coverage, TissueInfo achieves an accuracy of 76% for specificity and 89% for expression. For the same set of proteins, the curated tissue specificity offered in SWISS-PROT was accurate in 78% of cases. TissueInfo can be useful for the selection of clones for custom microarrays, selection of training sets for ab initio identification of tissue information, gene discovery and genome-wide predictions. Further information about the program can be found at http://icb.mssm.edu/tissueinfo.