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Advantages of the Bagidis methodology for metabonomics analyses: application to a spectroscopic study of Age-related Macular Degeneration
Timmermans, Catherine; De Tullio, Pascal; Lambert, Vincent et al.
2012In Proceedings of the 12th European Symposium on Statistical Methods for the Food Industry
Peer reviewed
 

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Keywords :
spectroscopy
Abstract :
[en] The Bagidis methodology proposes a distance measure between spectra, that takes into account, in a unified framework, both horizontal shifts and amplitudes variations that might affect spectral peaks. The method relies on the expansion of the spectra in unbalanced Haar wavelet bases. Its opportunity for investigating 1HNMR spectra in metabonomics is illustrated here in the framework of a study of an eye disease: age-related macular degeneration. Visual analysis, disease detection model and search for biomarkers are proposed here and compared with known methods.
Disciplines :
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Author, co-author :
Timmermans, Catherine ;  Université de Liège > Département de mathématique > Département de mathématique
De Tullio, Pascal ;  Université de Liège > Département de pharmacie > Chimie pharmaceutique
Lambert, Vincent;  Centre Hospitalier Universitaire de Liège - CHU
Frederich, Michel  ;  Université de Liège > Département de pharmacie > Pharmacognosie
Rousseau, Réjane;  Université Catholique de Louvain - UCL
von Sachs, Rainer;  Université Catholique de Louvain - UCL
Language :
English
Title :
Advantages of the Bagidis methodology for metabonomics analyses: application to a spectroscopic study of Age-related Macular Degeneration
Publication date :
29 February 2012
Event name :
12th European Symposium on Statistical Methods for the Food Industry
Event date :
du 29 février au 02 mars 2012
Audience :
International
Main work title :
Proceedings of the 12th European Symposium on Statistical Methods for the Food Industry
Peer reviewed :
Peer reviewed
Commentary :
12th European Symposium on Statistical Methods for the Food Industry
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