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:	1578
	Name:	1,3-diethyl 2-acetamidopropanedioate
	Description:
	Labels:	Neutral
	CAS:	1068-90-2
	InChi Code:	InChI=1/C9H15NO5/c1-4-14-8(12)7(10-6(3)11)9(13)15-5-2/h7H,4-5H2,1-3H3,(H,10,11)/f/h10H

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

Value	Source or prediction
-1.2	experimental value
-0.77	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
0.1	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
-1.19	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
-0.54	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
-0.38	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
-0.19	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
-1.18	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
-0.6	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
-1.13	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
-0.9	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
-1.35	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
-0.41	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)