Personalized medicine is to deliver the right drug to the right patient in the right dose. Pharmacogenomics (PGx), the studies in identifying genetic variants that may affect drug response, is important for personalized medicine. Computational approaches in studying the relationships between genes and drug response are emerging as an active area of research for personalized medicine. Currently, systematic study of drug-gene relationships is limited because a large-scale machine understandable drug-gene relationship knowledge base is difficult to build and to keep update. Scientific literature contains rich information of drug-gene relationships, therefore is the ultimate knowledge source for PGx studies and for personalized medicine. Rong Xu, A Semi-Supervised Pattern-Learning Approach to Extract Pharmacogenomics-Specific Drug-Gene Pairs from Biomedical Literature.

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