Genetic Programming as an Analytical Tool for Metabolome Data

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@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 = "http://www.cs.ucl.ac.uk/staff/W.Langdon/eebic/eurogp99/eurogp99_lbp.html",
• 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

Citations