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Article Dans Une Revue Journal of Biomedical Informatics Année : 2015

Comparative analysis of targeted metabolomics : dominance-based rough set approach versus orthogonal partial least square-discriminant analysis

Résumé

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients.
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hal-01233551 , version 1 (21-02-2022)

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Hélène Blasco, Jerzy Blaszczynski, Jean-Charles Billaut, Lydie Nadal-Desbarats, Pierre-Francois Pradat, et al.. Comparative analysis of targeted metabolomics : dominance-based rough set approach versus orthogonal partial least square-discriminant analysis. Journal of Biomedical Informatics, 2015, 53, pp.291-299. ⟨10.1016/j.jbi.2014.12.001⟩. ⟨hal-01233551⟩
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