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:1539
Name:2-phenylpropan-1-ol
Description:
Labels:Neutral
CAS:1123-85-9
InChi Code:InChI=1/C9H12O/c1-8(7-10)9-5-3-2-4-6-9/h2-6,8,10H,7H2,1H3/t8?

Properties

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

ValueSource or prediction
-0.4

experimental value

-0.3

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

-0.11

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

-0.39

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

-0.35

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

-0.26

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

-0.27

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

-0.42

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

-0.33

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

-0.4

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

-0.34

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

-0.41

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

-0.33

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