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:	1246
	Name:	2-bromo-N-(2-hydroxy-5-nitrophenyl)acetamide
	Description:
	Labels:	Neutral
	CAS:	3947-58-8
	InChi Code:	InChI=1/C8H7BrN2O4/c9-4-8(13)10-6-3-5(11(14)15)1-2-7(6)12/h1-3,12H,4H2,(H,10,13)/f/h10H

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

Value	Source or prediction
0.87	experimental value
1.2	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
2.01	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
0.88	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
1.89	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
1.38	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
1.35	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
0.89	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
1.96	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
0.98	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
1.97	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
0.75	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
1.54	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)