Predicting toxic equivalence factors from 13C nuclear magnetic resonance spectra for dioxins, furans, and polychlorinated biphenyls using linear and nonlinear pattern recognition methods

Environmental Toxicology and Chemistry

Volumn 23, Issue 1, 2004, Pages 24-31

  Buzatu, Dan A ^a   Beger, Richard D ^a   Wilkes, Jon G ^a   Lay Jr , Jackson O ^a  

^a NATIONAL CENTER FOR TOXICOLOGICAL RESEARCH   (United States)

Author keywords

Dioxin; Spectroscopic data activity relationship

Indexed keywords

BIOCHEMISTRY; ELECTROSTATICS; FURAN RESINS; MOLECULAR ORIENTATION; NEURAL NETWORKS; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PATTERN RECOGNITION; POLYCHLORINATED BIPHENYLS; QUANTUM THEORY; REGRESSION ANALYSIS;

BIOCHEMICAL PROPERTIES;

TOXICITY;

DIOXIN; FURAN DERIVATIVE; POLYCHLORINATED BIPHENYL;

DIOXIN; NUCLEAR MAGNETIC RESONANCE; PCB; TOXICITY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CARBON NUCLEAR MAGNETIC RESONANCE; ELECTRIC POTENTIAL; MODEL; NONLINEAR SYSTEM; PATTERN RECOGNITION; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; QUANTUM MECHANICS; STRUCTURE ACTIVITY RELATION; TOXICITY TESTING; VALIDATION PROCESS;

ANIMALS; CARBON ISOTOPES; DIOXINS; ENVIRONMENTAL POLLUTANTS; FORECASTING; FURANS; LINEAR MODELS; MAGNETIC RESONANCE SPECTROSCOPY; PATTERN RECOGNITION, AUTOMATED; POLYCHLORINATED BIPHENYLS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

COSA;

EID: 0347989546     PISSN: 07307268     EISSN: None     Source Type: Journal    
DOI: 10.1897/02-516     Document Type: Article

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