| Автор | Chung, K K |
| Автор | Do, D Q |
| Дата выпуска | 2010-09-01 |
| dc.description | In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data. |
| Формат | application.pdf |
| Издатель | Institute of Physics Publishing |
| Копирайт | 2010 Vietnam Academy of Science & Technology |
| Название | Modelling the effect of structural QSAR parameters on skin penetration using genetic programming |
| Тип | paper |
| DOI | 10.1088/2043-6254/1/3/035003 |
| Electronic ISSN | 2043-6262 |
| Print ISSN | 2043-6254 |
| Журнал | Advances in Natural Sciences: Nanoscience and Nanotechnology |
| Том | 1 |
| Первая страница | 35003 |
| Последняя страница | 35009 |
| Аффилиация | Chung, K K; Faculty of Pharmacy, University of Medicine and Pharmacy in Ho Chi Minh City, Vietnam |
| Аффилиация | Do, D Q; Faculty of Pharmacy, University of Medicine and Pharmacy in Ho Chi Minh City, Vietnam |
| Выпуск | 3 |
