In silico prediction of chemical toxicity on avian species using chemical category approaches

Chemosphere

Volumn 122, Issue , 2015, Pages 280-287

  Zhang, Chen ^a   Cheng, Feixiong ^a,c   Sun, Lu ^a   Zhuang, Shulin ^b   Li, Weihua ^a   Liu, Guixia ^a   Lee, Philip W ^a   Tang, Yun ^a  

^a EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b ZHEJIANG UNIVERSITY   (China)

^c VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

Avian toxicity; Chemical category approach; In silico prediction; Information gain; Support vector machine

Indexed keywords

BIRDS; ENVIRONMENTAL PROTECTION AGENCY; FORECASTING; INDUSTRIAL CHEMICALS; SUPPORT VECTOR MACHINES; TOXICITY;

CLASSIFICATION CRITERION; IN-SILICO; INFORMATION GAIN; MACHINE LEARNING METHODS; MOLECULAR DESCRIPTORS; OVERALL ACCURACIES; TOXICITY PREDICTIONS; UNITED STATES ENVIRONMENTAL PROTECTION AGENCIES;

INDICATORS (CHEMICAL);

ACID ANHYDRIDE; AMIDINE; CARBAMIC ACID DERIVATIVE; LACTONE; PHOSPHORIC ACID DERIVATIVE; SULFOXIDE; TOXIC SUBSTANCE; URETHAN; POLLUTANT;

ACCURACY ASSESSMENT; BIRD; CHEMICAL POLLUTANT; CLASSIFICATION; PESTICIDE; POLLUTION MONITORING; SPECIES DIVERSITY; TOXICITY;

ANAS PLATYRHYNCHOS; ARTICLE; BAYESIAN LEARNING; CHEMICAL SAFETY; COMPUTER MODEL; K NEAREST NEIGHBOR; MACHINE LEARNING; NONHUMAN; QUAIL; RANDOM FOREST; SUPPORT VECTOR MACHINE; ANIMAL; BIRD; COMPUTER SIMULATION; ECOTOXICOLOGY; GOVERNMENT; LD50; POLLUTANT; THEORETICAL MODEL; TOXICITY; UNITED STATES;

ANAS PLATYRHYNCHOS; AVES; COLINUS VIRGINIANUS; COTURNIX JAPONICA;

ANIMALS; BIRDS; CHEMICAL SAFETY; COMPUTER SIMULATION; ECOTOXICOLOGY; ENVIRONMENTAL POLLUTANTS; LETHAL DOSE 50; MODELS, THEORETICAL; SUPPORT VECTOR MACHINES; UNITED STATES; UNITED STATES ENVIRONMENTAL PROTECTION AGENCY;

EID: 84920547881     PISSN: 00456535     EISSN: 18791298     Source Type: Journal    
DOI: 10.1016/j.chemosphere.2014.12.001     Document Type: Article

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