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Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation

Hochrein, Jochen, Zacharias, Helena, Taruttis, Franziska, Samol, Claudia, Engelmann, Julia C., Spang, Rainer, Oefner, Peter J. and Gronwald, Wolfram (2015) Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation. J. Proteome Res. 14 (8), pp. 3217-3228.

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Other URL: http://pubs.acs.org/doi/abs/10.1021/acs.jproteome.5b00192


Abstract

Data normalization is an essential step in NMR-based metabolomics. Conducted properly, it improves data quality and removes unwanted biases. The choice of the appropriate normalization method is critical and depends on the inherent properties of the data set in question. In particular, the presence of unbalanced metabolic regulation, where the different specimens and cohorts under investigation ...

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Item type:Article
Date:7 August 2015
Institutions:Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner)
Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Identification Number:
ValueType
10.1021/acs.jproteome.5b00192DOI
Keywords:NMR; data normalization; metabolomics; unbalanced regulation; confounding factors
Dewey Decimal Classification:600 Technology > 610 Medical sciences Medicine
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:33527
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