The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species

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@Article{taylor:1998:dpmsGP:aises,
  author =       "Janet Taylor and Royston Goodacre and 
                 William G. Wade and Jem J. Rowland and Douglas B. Kell",
  title =        "The deconvolution of pyrolysis mass spectra using
                 genetic programming: application to the identification
                 of some Eubacterium species",
  journal =      "FEMS Microbiology Letters",
  year =         "1998",
  volume =       "160",
  pages =        "237--246",
  organisation = "Federation of European Microbiological Societies",
  publisher =    "Elsevier Science",
  keywords =     "genetic algorithms, genetic programming, Chemometrics,
                 Eubacterium, pyrolysis mass spectrometry",
  size =         "10 pages",
  DOI =          "doi:10.1016/S0378-1097(98)00038-X",
  abstract =     "Pyrolysis mass spectrometry was used to produce
                 complex biochemical fingerprints of Eubacterium
                 exiguum, E. infirmum, E. tardum and E. timidum. To
                 examine the relationship between these organisms the
                 spectra were clustered by canonical variates analysis,
                 and four clusters, one for each species, were observed.
                 In an earlier study we trained artificial neural
                 networks to identify these clinical isolates
                 successfully; however, the information used by the
                 neural network was not accessible from this so-called
                 'black box' technique. To allow the deconvolution of
                 such complex spectra (in terms of which masses were
                 important for discrimination) it was necessary to
                 develop a system that itself produces 'rules' that are
                 readily comprehensible. We here exploit the
                 evolutionary computational technique of genetic
                 programming; this rapidly and automatically produced
                 simple mathematical functions that were also able to
                 classify organisms to each of the four bacterial groups
                 correctly and unambiguously. Since the rules used only
                 a very limited set of masses, from a search space some
                 50 orders of magnitude greater than the dimensionality
                 actually necessary, visual discrimination of the
                 organisms on the basis of these spectral masses alone
                 was also then possible.",
  notes =        "

                 PMID: 9532743",
}

Genetic Programming entries for Janet Taylor Royston Goodacre William G Wade Jem J Rowland Douglas B Kell

Citations