Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | t1364 | |
|---|---|---|
| Name: | C12-14-Alkyl glycidyl ether | |
| Description: | ||
| Labels: | ||
| CAS: | 68609-97-2 | |
| InChi Code: | InChI=1S/C15H30O2/c1-2-3-4-5-6-7-8-9-10-11-12-16-13-15-14-17-15/h15H,2-14H2,1H3 |
Properties
er_ago: Activity in ER agonist pathway
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| inactive |
Tab3.agonists: Model for ER activity on agonists pathway (Training set) |
| inactive |
Tab3.agonists: Model for ER activity on agonists pathway (Out of bag) |
er_ant: Activity in ER antagonist pathway
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| inactive |
Tab3.antagonists: Model for ER activity on antagonists pathway (Training set) |
| inactive |
Tab3.antagonists: Model for ER activity on antagonists pathway (Out of bag) |
er_bin: Binding activity in estrogen receptor
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| inactive |
Tab3.binders: Model for binding in ER (Training set) |
| inactive |
Tab3.binders: Model for binding in ER (Out of bag) |