title: Application of genetic algorithm-kernel partial least square as a novel non-linear feature selection method: partitioning of drug molecules.
abstract: Genetic algorithm (GA) and partial least squares (PLS) and kernel PLS (KPLS) techniques were used to investigate the correlation between immobilized liposome chromatography partitioning (log Ks) and descriptors for 65 drug compounds. The models were validated using leave-group-out cross validation LGO-CV. The results indicate that GA-KPLS can be used as an alternative modelling tool for quantitative structure-property relationship (QSPR) studies.
authors: Islamic Azad University, Ilam Branch, Ilam, Iran. hadinoorizadeh@yahoo.com
authors: H
authors: H
authors: Noorizadeh
authors: S
authors: S
authors: Sobhan Ardakani
authors: T
authors: T
authors: Ahmadi
authors: S S
authors: SS
authors: Mortazavi
authors: M
authors: M
authors: Noorizadeh
mesh_terms: D000465:Algorithms; D002845:Chromatography / Q000379:methods; D016018:Least-Squares Analysis; D008081:Liposomes / Q000737:chemistry; D008956:Models, Chemical; D016571:Neural Networks, Computer; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D008081:Liposomes; D004364:Pharmaceutical Preparations