Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism

Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to ju...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Michiel Bongaerts, Ramon Bonte, Serwet Demirdas, Edwin H. Jacobs, Esmee Oussoren, Ans T. van der Ploeg, Margreet A. E. M. Wagenmakers, Robert M. W. Hofstra, Henk J. Blom, Marcel J. T. Reinders, George J. G. Ruijter
Μορφή: Άρθρο
Γλώσσα:English
Έκδοση: MDPI AG 2020-12-01
Σειρά:Metabolites
Θέματα:
untargeted metabolomics
inborn errors of metabolism
normalization
internal standards
batch effects
Διαθέσιμο Online:https://www.mdpi.com/2218-1989/11/1/8

Διαδίκτυο

https://www.mdpi.com/2218-1989/11/1/8

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