Exploiting Literature-derived Knowledge and Semantics to Identify Potential Prostate Cancer Drugs

Exploiting Literature-derived Knowledge and Semantics to Identify Potential Prostate Cancer Drugs

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In this study, we report on the performance of an automated approach to discovery of potential prostate cancer drugs from the biomedical literature. We used the semantic relationships in SemMedDB, a database of structured knowledge extracted from all MEDLINE citations using SemRep, to extract potent...

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Bibliographic Details
Main Authors:	Rui Zhang, Michael J. Cairelli, Marcelo Fiszman, Halil Kilicoglu, Thomas C. Rindflesch, Serguei V. Pakhomov, Genevieve B. Melton
Format:	Article
Language:	English
Published:	SAGE Publishing 2014-01-01
Series:	Cancer Informatics
Online Access:	https://doi.org/10.4137/CIN.S13889

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