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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...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | Metabolites |
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| Κύριοι συγγραφείς: | , , , , , , , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
MDPI
2020
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7824495/ https://ncbi.nlm.nih.gov/pubmed/33375624 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/metabo11010008 |
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