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:1398
Name:butan-2-yl (2E)-but-2-enoate
Description:
Labels:Neutral
CAS:10371-45-6
InChi Code:InChI=1/C8H14O2/c1-4-6-8(9)10-7(3)5-2/h4,6-7H,5H2,1-3H3/b6-4+/t7?

Properties

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

ValueSource or prediction
-0.42

experimental value

-0.3

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

-0.09

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

-0.19

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

-0.05

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

-0.45

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

-0.43

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

-0.38

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

-0.2

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

-0.23

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

-0.12

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

-0.39

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

-0.26

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