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:	1989
	Name:	2,5-diphenylcyclohexa-2,5-diene-1,4-dione
	Description:
	Labels:	Neutral
	CAS:	844-51-9
	InChi Code:	InChI=1/C18H12O2/c19-17-12-16(14-9-5-2-6-10-14)18(20)11-15(17)13-7-3-1-4-8-13/h1-12H

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

Value	Source or prediction
1.48	experimental value
1.7	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
1.93	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
1.49	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
2.23	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
1.7	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
1.68	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
1.57	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.06	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
1.72	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
2.75	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
1.44	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
2.34	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)