10967/264 - QDB Compounds

QsarDB Repository

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:1609
Name:octylthiourea
Description:
Labels:Neutral
CAS:13281-03-3
InChi Code:InChI=1/C9H20N2S/c1-2-3-4-5-6-7-8-11-9(10)12/h2-8H2,1H3,(H3,10,11,12)/f/h11H,10H2

Properties

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

ValueSource or prediction
1.51

experimental value

1.35

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)

1.2

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)

1.44

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)

1.39

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)

1.44

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)

1.29

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)

1.53

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)

1.28

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)

1.48

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)

1.43

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)

1.51

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)

1.39

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)