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:	1686
	Name:	4-(prop-2-enoyloxy)butan-2-yl prop-2-enoate
	Description:
	Labels:	Neutral
	CAS:	19485-03-1
	InChi Code:	InChI=1/C10H14O4/c1-4-9(11)13-7-6-8(3)14-10(12)5-2/h4-5,8H,1-2,6-7H2,3H3/t8?

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

Value	Source or prediction
1.14	experimental value
0.89	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.43	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
1.13	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
0.45	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
0.67	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
0.65	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
1.15	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
0.79	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
1.21	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
0.83	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
1.08	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
0.63	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)