Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{goodacre:2003:cdupx,
  author =       "Royston Goodacre and Emma V. York and 
                 James K. Heald and Ian M. Scott",
  title =        "Chemometric discrimination of unfractionated plant
                 extracts analyzed by electrospray mass spectrometry",
  journal =      "Phytochemistry",
  year =         "2003",
  volume =       "62",
  number =       "6",
  pages =        "859--863",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Pharbitis
                 nil, Convolvulaceae, Japanese Morning Glory,
                 Electrospray ionization mass spectrometry, Neural
                 networks, Metabolic fingerprinting",
  URL =          "http://www.sciencedirect.com/science/article/B6TH7-47WBXD4-7/2/91ff09f988be54824c55a1cb596f7839",
  DOI =          "doi:10.1016/S0031-9422(02)00718-5",
  abstract =     "Metabolic fingerprints were obtained from
                 unfractionated Pharbitis nil leaf sap samples by direct
                 infusion into an electrospray ionization mass
                 spectrometer. Analyses took less than 30 s per sample
                 and yielded complex mass spectra. Various chemometric
                 methods, including discriminant function analysis and
                 the machine-learning methods of artificial neural
                 networks and genetic programming, could discriminate
                 the metabolic fingerprints of plants subjected to
                 different photoperiod treatments. This rapid automated
                 analytical procedure could find use in a variety of
                 phytochemical applications requiring high sample
                 throughput.",
  notes =        "GMax-Bio, Plant Metabolomics",
}

Genetic Programming entries for Royston Goodacre Emma V York James K Heald Ian M Scott

Citations