Classification of HIV protease inhibitors on the basis of their antiviral potency using radial basis function neural networks

Journal of Computer-Aided Molecular Design

Volumn 17, Issue 2-4, 2003, Pages 155-171

  Patankar, S J ^a   Jurs, P C ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Classification; GA; HIV protease inhibitors; k NN; Majority rules; QSAR; RBFNN classifier

Indexed keywords

COMPUTATIONAL CHEMISTRY; COST FUNCTIONS; DRUG THERAPY; GENETIC ALGORITHMS; NEAREST NEIGHBOR SEARCH; RADIAL BASIS FUNCTION NETWORKS;

ANTIVIRALS; GA; HIV PATIENTS; HIV-PROTEASE INHIBITORS; K-NN; MAJORITY RULE; NEURAL NETWORKS CLASSIFIERS; QSAR; RADIAL BASE FUNCTION NEURAL NETWORK CLASSIFIER; RADIAL BASIS FUNCTION NEURAL NETWORKS (RBF);

CLASSIFICATION (OF INFORMATION);

PROTEINASE INHIBITOR;

ALGORITHM; ANTIVIRAL ACTIVITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER MODEL; CONCENTRATION (PARAMETERS); DRUG CLASSIFICATION; DRUG POTENCY; DRUG STRUCTURE; HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MOLECULAR WEIGHT; NONHUMAN; PRIORITY JOURNAL; STRUCTURE ANALYSIS; VALIDATION PROCESS; VIRUS MUTANT; VIRUS REPLICATION; VIRUS STRAIN;

EID: 0042856583     PISSN: 0920654X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1025317806473     Document Type: Article

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