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We used the semantic relationships in SemMedDB, a database of structured knowledge extracted from all MEDLINE citations using SemRep, to extract potential relationships using knowledge of cancer drugs pathways. Two cancer drugs pathway schemas were constructed using these relationships extracted from SemMedDB. Trough both pathway schemas, we found drugs already used for prostate cancer therapy and drugs not currently listed as the prostate cancer medications. Our study demonstrates that the appropriate linking of relevant structured semantic relationships stored in SemMedDB can support the discovery of potential prostate cancer drugs.<\/jats:p>","DOI":"10.4137\/cin.s13889","type":"journal-article","created":{"date-parts":[[2014,10,14]],"date-time":"2014-10-14T17:52:16Z","timestamp":1413309136000},"page":"CIN.S13889","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Exploiting Literature-derived Knowledge and Semantics to Identify Potential Prostate Cancer Drugs"],"prefix":"10.4137","volume":"13s1","author":[{"given":"Rui","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA."},{"name":"Department of Surgery, University of Minnesota, Minneapolis, MN, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael 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