High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses.

@article{Jonsson2005HighthroughputDA,
  title={High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses.},
  author={P Andreas Jonsson and Annika I. Johansson and Jonas Gullberg and Johan Trygg and A Jiye and B. Grung and Stefan L Marklund and Michael Sj{\"o}str{\"o}m and Henrik Antti and Thomas Moritz},
  journal={Analytical chemistry},
  year={2005},
  volume={77 17},
  pages={
          5635-42
        }
}
In metabolomics, the objective is to identify differences in metabolite profiles between samples. A widely used tool in metabolomics investigations is gas chromatography-mass spectrometry (GC/MS). More than 400 compounds can be detected in a single analysis, if overlapping GC/MS peaks are deconvoluted. However, the deconvolution process is time-consuming and difficult to automate, and additional processing is needed in order to compare samples. Therefore, there is a need to improve and automate… CONTINUE READING
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