Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules
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...
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Englisch |
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2000 |
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16 |
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Springer Online Journal Archives 1860-2002 |
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in: Genetic programming and evolvable machines - 2000, 1(2000) vom: März, Seite 243-258 |
| Übergeordnetes Werk: |
volume:1 ; year:2000 ; month:03 ; pages:243-258 ; extent:16 |
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| 520 | |a 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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. | ||
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| 700 | 1 | |a Gilbert, Richard J. |4 oth | |
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| 700 | 1 | |a Smith, Aileen R. |4 oth | |
| 700 | 1 | |a Rowland, Jem J. |4 oth | |
| 700 | 1 | |a Hall, Michael A. |4 oth | |
| 700 | 1 | |a Kell, Douglas B. |4 oth | |
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(DE-627)NLEJ197306152 DE-627 ger DE-627 rakwb eng Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules 2000 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. Springer Online Journal Archives 1860-2002 Johnson, Helen E. oth Gilbert, Richard J. oth Winson, Michael K. oth Goodacre, Royston oth Smith, Aileen R. oth Rowland, Jem J. oth Hall, Michael A. oth Kell, Douglas B. oth in Genetic programming and evolvable machines 2000 1(2000) vom: März, Seite 243-258 (DE-627)NLEJ188989315 (DE-600)2015531-1 1573-7632 nnns volume:1 year:2000 month:03 pages:243-258 extent:16 http://dx.doi.org/10.1023/A:1010014314078 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 1 2000 3 243-258 16 |
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(DE-627)NLEJ197306152 DE-627 ger DE-627 rakwb eng Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules 2000 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. Springer Online Journal Archives 1860-2002 Johnson, Helen E. oth Gilbert, Richard J. oth Winson, Michael K. oth Goodacre, Royston oth Smith, Aileen R. oth Rowland, Jem J. oth Hall, Michael A. oth Kell, Douglas B. oth in Genetic programming and evolvable machines 2000 1(2000) vom: März, Seite 243-258 (DE-627)NLEJ188989315 (DE-600)2015531-1 1573-7632 nnns volume:1 year:2000 month:03 pages:243-258 extent:16 http://dx.doi.org/10.1023/A:1010014314078 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 1 2000 3 243-258 16 |
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(DE-627)NLEJ197306152 DE-627 ger DE-627 rakwb eng Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules 2000 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. Springer Online Journal Archives 1860-2002 Johnson, Helen E. oth Gilbert, Richard J. oth Winson, Michael K. oth Goodacre, Royston oth Smith, Aileen R. oth Rowland, Jem J. oth Hall, Michael A. oth Kell, Douglas B. oth in Genetic programming and evolvable machines 2000 1(2000) vom: März, Seite 243-258 (DE-627)NLEJ188989315 (DE-600)2015531-1 1573-7632 nnns volume:1 year:2000 month:03 pages:243-258 extent:16 http://dx.doi.org/10.1023/A:1010014314078 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 1 2000 3 243-258 16 |
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(DE-627)NLEJ197306152 DE-627 ger DE-627 rakwb eng Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules 2000 16 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. Springer Online Journal Archives 1860-2002 Johnson, Helen E. oth Gilbert, Richard J. oth Winson, Michael K. oth Goodacre, Royston oth Smith, Aileen R. oth Rowland, Jem J. oth Hall, Michael A. oth Kell, Douglas B. oth in Genetic programming and evolvable machines 2000 1(2000) vom: März, Seite 243-258 (DE-627)NLEJ188989315 (DE-600)2015531-1 1573-7632 nnns volume:1 year:2000 month:03 pages:243-258 extent:16 http://dx.doi.org/10.1023/A:1010014314078 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 1 2000 3 243-258 16 |
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Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules |
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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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. |
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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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. |
| abstract_unstemmed |
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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ197306152</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210705212345.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">070527s2000 xx |||||o 00| ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ197306152</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Explanatory Analysis of the Metabolome Using Genetic Programming of Simple, Interpretable Rules</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2000</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">16</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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 of whole tissue extracts are not amenable to direct visual analysis, so numerical modelling methods were used to generate models capable of classifying the samples based on their spectral characteristics. Genetic programming (GP) provided models with a better prediction accuracy to the conventional data modelling methods used, whilst being much easier to interpret in terms of the variables used. Examination of the GP-derived models showed that there were 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 that, in this study, improves our understanding of the biochemistry of salt tolerance in tomato plants.</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="f">Springer Online Journal Archives 1860-2002</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Johnson, Helen E.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gilbert, Richard J.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Winson, Michael K.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Goodacre, Royston</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Smith, Aileen R.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rowland, Jem J.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hall, Michael A.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kell, Douglas B.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">in</subfield><subfield code="t">Genetic programming and evolvable machines</subfield><subfield code="d">2000</subfield><subfield code="g">1(2000) vom: März, Seite 243-258</subfield><subfield code="w">(DE-627)NLEJ188989315</subfield><subfield code="w">(DE-600)2015531-1</subfield><subfield code="x">1573-7632</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:1</subfield><subfield code="g">year:2000</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:243-258</subfield><subfield code="g">extent:16</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1023/A:1010014314078</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-SOJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_NL_ARTICLE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">1</subfield><subfield code="j">2000</subfield><subfield code="c">3</subfield><subfield code="h">243-258</subfield><subfield code="g">16</subfield></datafield></record></collection>
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