Detalle de: Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model
| Title | Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model |
| Abstract |
The CODES/neural network model has been successfully applied to the prediction of pharmacokinetic properties of therapeutical compounds. The output of CODES, a graphical module based on the Gestalt isomorphism, is proved to be a valuable tool in the design of a neural network model able to predict the half-life values of antihistamines. Additionally, the generated models are able to classify these drugs in their corresponding therapeutic category (H1 or H2 receptor antagonists). |
| Apa Reference | Quiñones, C., Caceres, J., Stud, M. & Martinez, A. (2000). Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model. Quantitative Structure-Activity Relationship, 19(5), 448-454. 10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3 |
| Doi | 10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3 |
| Publication Date | Dec 2000 |
| Publication Type | Article |
| Researcher | Ana Martínez |
| Ontology | Artificial Intelligence, Deep Learning in Biology |
| Research Groups | |
| Tools |