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:1672
Name:(1S)-1-phenylbutan-1-ol
Description:
Labels:Neutral
CAS:22135-49-5
InChi Code:InChI=1/C10H14O/c1-2-6-10(11)9-7-4-3-5-8-9/h3-5,7-8,10-11H,2,6H2,1H3/t10-/m0/s1

Properties

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

ValueSource or prediction
-0.09

experimental value

-0.01

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

0.06

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

-0.02

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

-0.04

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

-0.09

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

-0.0

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

-0.04

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

-0.01

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

0.01

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

-0.04

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

-0.02

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

0.02

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