Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.

Compound

	ID:	1925
	Name:	N-benzyl-4-methylpyridin-2-amine
	Description:
	Labels:	Neutral
	CAS:	58088-62-3
	InChi Code:	InChI=1/C13H14N2/c1-11-7-8-14-13(9-11)15-10-12-5-3-2-4-6-12/h2-9H,10H2,1H3,(H,14,15)/f/h15H

pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i

Value	Source or prediction
0.95	experimental value
0.97	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.93	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
0.94	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
0.75	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
0.96	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
0.63	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
0.87	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
0.88	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
0.77	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
0.76	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
1.0	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
0.85	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)