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:1194
Name:benzene-1,2-dicarbonitrile
Description:
Labels:Neutral
CAS:91-15-6
InChi Code:InChI=1/C8H4N2/c9-5-7-3-1-2-4-8(7)6-10/h1-4H

Properties

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

ValueSource or prediction
-0.34

experimental value

-0.19

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)

-0.33

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)

-0.19

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

-0.1

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

-0.23

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

0.3

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

-0.33

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

-0.14

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)

0.02

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