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Avoiding hard chromatographic segmentation: A moving window approach for the automated resolution of gas chromatography–mass spectrometry-based metabolomics signals by multivariate methods

Author
Domingo, X.; Perera, A.; Brezmes, J.
Type of activity
Journal article
Journal
Journal of chromatography A
Date of publication
2016-11-25
Volume
1474
First page
145
Last page
151
DOI
https://doi.org/10.1016/j.chroma.2016.10.066 Open in new window
Repository
http://hdl.handle.net/2117/99562 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0021967316314315 Open in new window
Abstract
Gas chromatography–mass spectrometry (GC–MS) produces large and complex datasets characterized by co-eluted compounds and at trace levels, and with a distinct compound ion-redundancy as a result of the high fragmentation by the electron impact ionization. Compounds in GC–MS can be resolved by taking advantage of the multivariate nature of GC–MS data by applying multivariate resolution methods. However, multivariate methods have to be applied in small regions of the chromatogram, and ther...
Citation
Domingo, X., Perera, A., Brezmes, J. Avoiding hard chromatographic segmentation: A moving window approach for the automated resolution of gas chromatography–mass spectrometry-based metabolomics signals by multivariate methods. "Journal of chromatography A", 25 Novembre 2016, vol. 1474, p. 145-151.
Keywords
gas chromatography, independent component analysis, metabolomics, moving window, multivariate curve resolution, orthogonal signal deconvolution
Group of research
B2SLab - Bioinformatics and Biomedical Signals Laboratory
CREB - Biomedical Engineering Research Centre

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