Use of quantitative-structure property relationship (QSPR) and artificial neural network (ANN) based approaches for estimating the octanol-water partition coefficients of the 209 chlorinated trans-azobenzene congeners

Journal of Environmental Science and Health - Part B Pesticides, Food Contaminants, and Agricultural Wastes

Volumn 47, Issue 2, 2012, Pages 111-128

  Wilczyńska Piliszek, Agata J ^a   Piliszek, Sławomir ^a   Falandysz, Jerzy ^a  

^a UNIVERSITY OF GDA SK   (Poland)

Author keywords

bioaccumulation; chloro trans azobenzenes; Ct ABs; environmental fate; partition coefficients; PCABs; Polychlorinated azobenzenes; POPs

Indexed keywords

CHLORO TRANS-AZOBENZENES; CT-ABS; ENVIRONMENTAL FATE; PARTITION COEFFICIENT; PCABS; POPS;

ALCOHOLS; AZOBENZENE; BIOACCUMULATION; BIOCHEMISTRY; CHEMICAL PROPERTIES; DENSITY FUNCTIONAL THEORY; HERBICIDES; MOLECULAR ORBITALS; NEURAL NETWORKS; POLYCHLORINATED BIPHENYLS; UREA;

ORGANIC POLLUTANTS;

ARTIFICIAL NEURAL NETWORK; BIOACCUMULATION; DIURON; ENVIRONMENTAL FATE; GAUSSIAN METHOD; GEOMETRY; MOBILITY; OPTIMIZATION; PARTITION COEFFICIENT; PCB; PCDD; PCDF; QUANTITATIVE ANALYSIS;

TETRA;

AZO COMPOUND; AZOBENZENE; DIBENZO(1,4)DIOXIN; DIOXIN; OCTANOL; POLYCHLORINATED BIPHENYL; WATER;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMISTRY; COMPUTER PROGRAM; COMPUTER SIMULATION; HALOGENATION; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

1-OCTANOL; ALGORITHMS; AZO COMPOUNDS; COMPUTER SIMULATION; DIOXINS; HALOGENATION; NEURAL NETWORKS (COMPUTER); POLYCHLORINATED BIPHENYLS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOFTWARE; WATER;

EID: 84859354142     PISSN: 03601234     EISSN: 15324109     Source Type: Journal    
DOI: 10.1080/03601234.2012.616779     Document Type: Article

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