Genetic Programming as an Analytical Tool for Metabolome Data

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

@InProceedings{gilbert:1999:,
  author =       "Richard J. Gilbert and Helen E. Johnson and 
                 Michael K. Winson and Jem J. Rowland and Royston Goodacre and 
                 Aileen R. Smith and Michael A. Hall and 
                 Douglas B. Kell",
  title =        "Genetic Programming as an Analytical Tool for
                 Metabolome Data",
  booktitle =    "Late-Breaking Papers of EuroGP-99",
  year =         "1999",
  editor =       "W. B. Langdon and Riccardo Poli and Peter Nordin and 
                 Terry Fogarty",
  pages =        "23--33",
  address =      "Goteborg, Sweden",
  month =        "26-27 " # may,
  organisation = "EvoGP",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.cwi.nl/pub/CWIreports/SEN/SEN-R9913.pdf",
  URL =          "ftp://ftp.cwi.nl/pub/CWIreports/SEN/SEN-R9913.ps.Z",
  abstract =     "Genetic programming, in conjunction with advanced
                 analytical instruments, is a novel tool for the
                 investigation of complex biological systems at the
                 whole-tissue level.

                 In this study, samples from tomato fruit grown
                 hydroponically under both high- and low-salt conditions
                 were analysed using Fourier-transform infrared
                 spectroscopy (FTIR), with the aim of identifying
                 spectral and biochemical features linked to salinity in
                 the growth environment.

                 FTIR spectra are not amenable to direct visual
                 analysis, so supervised machine learning was used to
                 generate models capable of classifying the samples
                 based on their spectral characteristics. The genetic
                 programming (GP) method was chosen, since it has
                 previously been shown to perform with the same accuracy
                 as conventional data modelling methods, but in a
                 readily-interpretable form.

                 Examination of the GP-derived models showed that there
                 was a small number of spectral regions that were
                 consistently being used. In particular, the spectral
                 region containing absorbances potentially due to a
                 cyanide/nitrile functional group was identified as
                 discriminatory. The explanatory power of the GP models
                 enabled a chemical interpretation of the biochemical
                 differences to be proposed. The combination of FTIR and
                 GP is therefore a powerful and novel analytical tool
                 which, in this study, improves our understanding of the
                 biochemistry of salt tolerance in tomato plants.",
  notes =        "EuroGP'99LB part of \cite{langdon:1999:egplb}",
}

Genetic Programming entries for Richard J Gilbert Helen E Johnson Michael K Winson Jem J Rowland Royston Goodacre Aileen R Smith Michael A Hall Douglas B Kell

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