Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques

The aim of this work was the comparison between k-Nearest Neighbors (k-NN) and Counterpropagation Artificial Neural network (CP-ANN) classification methods for modeling the toxicity of a set of 192 organochlorinated, organophosphates, carbamates, and pyrethroid pesticides measured as effective conce...

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Autores principales: Cárdenas, Fernando, Tripaldi, Piercosimo, Rojas Villa, Cristian Xavier
Formato: Articulo
Lenguaje:Español
Publicado: 2014
Materias:
Química
Pesticides
k-NN
CP-ANN
GA-VSS
QSAR Theory
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/112921
https://revistas.usfq.edu.ec/index.php/avances/article/view/169
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-112921
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Español
topic Química
Pesticides
k-NN
CP-ANN
GA-VSS
QSAR Theory
spellingShingle Química
Pesticides
k-NN
CP-ANN
GA-VSS
QSAR Theory
Cárdenas, Fernando
Tripaldi, Piercosimo
Rojas Villa, Cristian Xavier
Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
topic_facet Química
Pesticides
k-NN
CP-ANN
GA-VSS
QSAR Theory
description The aim of this work was the comparison between k-Nearest Neighbors (k-NN) and Counterpropagation Artificial Neural network (CP-ANN) classification methods for modeling the toxicity of a set of 192 organochlorinated, organophosphates, carbamates, and pyrethroid pesticides measured as effective concentration (EC50). The EC50 values were divided into three classes, i.e. low, intermediate, and high toxicity. The 4885 molecular descriptors were calculated using the Dragon software, and then were simultaneously analyzed through k-NN classification analysis coupled with Genetic Algorithms - Variable Subset Selection (GA-VSS) technique. The models were properly validated through an external test set of compounds. The results clearly suggest that 3D-descriptors did not offer relevant information for modeling the classes. On the other hand, k-NN showed better results than CP-ANN.
format Articulo
Articulo
author Cárdenas, Fernando
Tripaldi, Piercosimo
Rojas Villa, Cristian Xavier
author_facet Cárdenas, Fernando
Tripaldi, Piercosimo
Rojas Villa, Cristian Xavier
author_sort Cárdenas, Fernando
title Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
title_short Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
title_full Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
title_fullStr Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
title_full_unstemmed Quantitative Structure-Activity Relationship study for pesticides by means of classification techniques
title_sort quantitative structure-activity relationship study for pesticides by means of classification techniques
publishDate 2014
url http://sedici.unlp.edu.ar/handle/10915/112921
https://revistas.usfq.edu.ec/index.php/avances/article/view/169
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