Combining PLS with GA-GP for QSAR

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Tang:2002:CILS,
  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.",
}

Genetic Programming entries for Kailin Tang Tonghua Li

Citations