{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T11:36:19Z","timestamp":1784115379728,"version":"3.55.0"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>We describe a method to identify candidate cancer biomarkers by analyzing numeric approximations of tissue specificity of human genes. These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human genome sequence using a binary indexing algorithm. Tissue-specificity values facilitated high-throughput analysis of the human genes and enabled the identification of genes highly specific to different tissues. Tissue expression distributions for several genes were compared to estimates obtained from other public gene expression datasets and experimentally validated using quantitative RT-PCR on RNA isolated from several human tissues. Our results demonstrate that most human genes (\u223c98%) are expressed in many tissues (low specificity), and only a small number of genes possess very specific tissue expression profiles. These genes comprise a rich dataset from which novel therapeutic targets and novel diagnostic serum biomarkers may be selected.<\/jats:p><jats:p>Contact: vasm@mayo.edu<\/jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btm102","type":"journal-article","created":{"date-parts":[[2007,3,24]],"date-time":"2007-03-24T00:22:51Z","timestamp":1174695771000},"page":"1348-1355","source":"Crossref","is-referenced-by-count":16,"title":["Quantitating tissue specificity of human genes to facilitate biomarker discovery"],"prefix":"10.1093","volume":"23","author":[{"given":"George","family":"Vasmatzis","sequence":"first","affiliation":[{"name":"1 Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, 200 First St. SW, Rochester, MN 55905, USA and 2Division of Biostatistics, Health Sciences Research, Mayo Clinic, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric W.","family":"Klee","sequence":"additional","affiliation":[{"name":"1 Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, 200 First St. SW, Rochester, MN 55905, USA and 2Division of Biostatistics, Health Sciences Research, Mayo Clinic, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dagmar M.","family":"Kube","sequence":"additional","affiliation":[{"name":"1 Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, 200 First St. SW, Rochester, MN 55905, USA and 2Division of Biostatistics, Health Sciences Research, Mayo Clinic, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Terry M.","family":"Therneau","sequence":"additional","affiliation":[{"name":"1 Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, 200 First St. SW, Rochester, MN 55905, USA and 2Division of Biostatistics, Health Sciences Research, Mayo Clinic, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farhad","family":"Kosari","sequence":"additional","affiliation":[{"name":"1 Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, 200 First St. SW, Rochester, MN 55905, USA and 2Division of Biostatistics, Health Sciences Research, Mayo Clinic, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2007,3,23]]},"reference":[{"key":"2023041104584128900_","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1093\/biomet\/35.3-4.246","article-title":"Transformations of poisson, binomial and negative-binomial data","volume":"35","author":"Anscombe","year":"1949","journal-title":"Biometrika"},{"key":"2023041104584128900_","first-page":"3308","article-title":"Identification of differentially expressed genes in normal and malignant prostate by electronic profiling of expressed sequence tags","volume":"62","author":"Asmann","year":"2002","journal-title":"Cancer Res."},{"key":"2023041104584128900_","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1056\/NEJM198310133091503","article-title":"A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer","volume":"309","author":"Bast","year":"1983","journal-title":"N. 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