Identifying predictive features in drug response using machine learning: Opportunities and challenges

Annual Review of Pharmacology and Toxicology

Volumn 55, Issue , 2015, Pages 15-34

  Vidyasagar, Mathukumalli ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

Cancer biology; EN algorithm; GSEA; k means clustering; LASSO; Machine learning; Neural networks; PAM; Precision medicine; Prediction in pharmacology; Regression; SAM; SVMs

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLASSIFICATION ALGORITHM; DRUG RESPONSE; GENE SET ENRICHMENT ANALYSIS; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR; MACHINE LEARNING; MICROARRAY ANALYSIS; PATTERN ANALYSIS FOR MICROARRAY; PRIORITY JOURNAL; REVIEW; RIDGE REGRESSION; SIGNIFICANCE ANALYSIS FOR MICROARRAY; SUPPORT VECTOR MACHINE; ALGORITHM; ANIMAL; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; DRUG DEVELOPMENT; DRUG EFFECTS; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; HUMAN; PATIENT SAFETY; PATIENT SELECTION; PERSONALIZED MEDICINE; PHARMACOLOGY; PROCEDURES; RISK ASSESSMENT; RISK FACTOR;

ANTINEOPLASTIC AGENT;

ALGORITHMS; ANIMALS; ANTINEOPLASTIC AGENTS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; DRUG DISCOVERY; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; GENE EXPRESSION REGULATION, NEOPLASTIC; GENE REGULATORY NETWORKS; HUMANS; INDIVIDUALIZED MEDICINE; NEURAL NETWORKS (COMPUTER); PATIENT SAFETY; PATIENT SELECTION; PATTERN RECOGNITION, AUTOMATED; PHARMACOLOGY; RISK ASSESSMENT; RISK FACTORS;

EID: 84920760734     PISSN: 03621642     EISSN: 15454304     Source Type: Book Series    
DOI: 10.1146/annurev-pharmtox-010814-124502     Document Type: Review

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