Combining PLS with GA-GP for QSAR

author = "Kailin Tang and Tonghua Li",

title = "Combining PLS with GA-GP for QSAR",

journal = "Chemometrics and Intelligent Laboratory Systems",

year = "2002",

volume = "64",

pages = "55--64",

number = "1",

keywords = "genetic algorithms, genetic programming, PLS, QSAR, Nonlinear modeling",

owner = "wlangdon",

URL = "

http://www.sciencedirect.com/science/article/B6TFP-46NXJ0Y-2/2/966def2759d210eea6e5312f9a0042c7",

ISSN = "0169-7439",

DOI = "

doi:10.1016/S0169-7439(02)00050-3",

abstract = "partial least squares (PLS) improved by genetic algorithm-genetic programming (GA-GP) is applied to deal with functions for inner relationship in quantitative structure-activity relationship (QSAR). PLS is used to build a linear or nonlinear model between the principal components and its activity, and GA-GP is applied to regressions and equations. It develops PLS models to increase the range of PLS modelling. Using the inner relationship of polynomial function, a set of 79 inhibitors of HIV-1 reverse transcriptase, derivatives of a recently reported HIV-1-specific lead: 1-[(2-hydroxyethoxy) methyl]-6-(phenylthio) thymine (HEPT) was studied. The obtained QSAR model shows high predictive ability, rcv=0.900. It demonstrates that this method is useful.",