ID: | 163 | |
---|---|---|
Name: | 2-chlorobutanoic acid | |
Description: | ||
Labels: | Neutral | |
CAS: | 4170-24-5 | |
InChi Code: | InChI=1/C4H7ClO2/c1-2-3(5)4(6)7/h3H,2H2,1H3,(H,6,7)/t3?/f/h6H |
pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i
Value | Source or prediction |
---|---|
-0.35 |
experimental value |
-0.4 |
RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set) |
-0.39 |
RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation) |
-0.36 |
SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set) |
-0.52 |
SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation) |
-0.48 |
KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set) |
-0.56 |
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) |
-0.61 |
XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation) |
-0.42 |
SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set) |
-0.75 |
SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation) |
-0.34 |
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) |