Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{goodacre:2003:cdupx,
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author = "Royston Goodacre and Emma V. York and
James K. Heald and Ian M. Scott",
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title = "Chemometric discrimination of unfractionated plant
extracts analyzed by electrospray mass spectrometry",
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journal = "Phytochemistry",
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year = "2003",
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volume = "62",
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number = "6",
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pages = "859--863",
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month = mar,
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keywords = "genetic algorithms, genetic programming, Pharbitis
nil, Convolvulaceae, Japanese Morning Glory,
Electrospray ionization mass spectrometry, Neural
networks, Metabolic fingerprinting",
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URL = "http://www.sciencedirect.com/science/article/B6TH7-47WBXD4-7/2/91ff09f988be54824c55a1cb596f7839",
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DOI = "doi:10.1016/S0031-9422(02)00718-5",
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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.",
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notes = "GMax-Bio, Plant Metabolomics",
- }
Genetic Programming entries for
Royston Goodacre
Emma V York
James K Heald
Ian M Scott
Citations