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State-of-the art data normalization methods improve NMR-based metabolomic analysis

Kohl, Stefanie M. ; Klein, Matthias S. ; Hochrein, Jochen ; Oefner, Peter J. ; Spang, Rainer ; Gronwald, Wolfram



Abstract

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This ...

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