C. Quiñones, Joaquín Caceres, M. Stud, Ana Martínez
{"title":"基于CODES/神经网络模型的抗组胺药半衰期预测","authors":"C. Quiñones, Joaquín Caceres, M. Stud, Ana Martínez","doi":"10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3","DOIUrl":null,"url":null,"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).","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model\",\"authors\":\"C. Quiñones, Joaquín Caceres, M. Stud, Ana Martínez\",\"doi\":\"10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3\",\"DOIUrl\":null,\"url\":null,\"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).\",\"PeriodicalId\":20818,\"journal\":{\"name\":\"Quantitative Structure-activity Relationships\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantitative Structure-activity Relationships\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Structure-activity Relationships","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/1521-3838(200012)19:5<448::AID-QSAR448>3.0.CO;2-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model
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).