Carcinogenicity modelling of diverse chemicals based on substructure grouping and support vector machines (CROSBI ID 559419)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Tanabe, Kazutoshi ; Lučić, Bono ; Amić, Dragan ; Suzuki, Takahiro
engleski
Carcinogenicity modelling of diverse chemicals based on substructure grouping and support vector machines
The prediction of carcinogenicity has become a subject of great significance for regulatory perspectives and ecotoxicity assessments. Several quantitative structure–activity relationship (QSAR) systems for predicting carcinogenicity were submitted to the Predictive Toxicology Challenge 2000–2001 Workshop ; however, the exercise revealed that performances of all proposed models were not sufficient in predicting carcinogenicities of test chemicals. In this study, an attempt was performed to construct a reliable QSAR model for predicting carcinogenicity of non- congeneric chemicals with a satisfactory performance. The support vector machines (SVM) approach was applied to develop QSAR models.
carcinogenicity ; QSAR ; support vector machines (SVM)
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Podaci o prilogu
A65-A66.
2009.
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objavljeno
Podaci o matičnoj publikaciji
Journal of pharmacy and pharmacology
Jones, D
London : Delhi: John Wiley & Sons
0022-3573
Podaci o skupu
The British Pharmaceutical Conference 2009
poster
06.09.2009-09.09.2009
Manchester, Ujedinjeno Kraljevstvo