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|a 10.1002/mrc.5350
|2 doi
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|a eng
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|a Jeppesen, Micah J
|e verfasserin
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|a Multiplatform untargeted metabolomics
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|c 2023
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|a Text
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|a ƒaComputermedien
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|a Date Completed 22.11.2023
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|a Date Revised 20.03.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2023 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.
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|a Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics
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|a Journal Article
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|a Review
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|a Research Support, N.I.H., Extramural
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|a mass spectrometry
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|a metabolite assignment
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| 650 |
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|a metabolome coverage
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|a metabolomics
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|a multiplatform
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|a nuclear magnetic resonance
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|a Powers, Robert
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|t Magnetic resonance in chemistry : MRC
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|g 61(2023), 12 vom: 08. Dez., Seite 628-653
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|u http://dx.doi.org/10.1002/mrc.5350
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