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:	1813
	Name:	2-phenylcyclohexa-2,5-diene-1,4-dione
	Description:
	Labels:	Neutral
	CAS:	363-03-1
	InChi Code:	InChI=1/C12H8O2/c13-10-6-7-12(14)11(8-10)9-4-2-1-3-5-9/h1-8H

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

Value	Source or prediction
2.83	experimental value
2.33	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
1.45	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
2.73	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
2.35	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
2.6	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
2.07	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
2.79	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
1.87	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
2.75	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
2.65	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
2.73	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
2.71	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)