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...

Descripció completa

Dades bibliogràfiques

Autors principals:	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
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-12-01
Col·lecció:	Metabolites
Matèries:	untargeted metabolomics inborn errors of metabolism normalization internal standards batch effects
Accés en línia:	https://www.mdpi.com/2218-1989/11/1/8
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!