Unknown Metabolite Identification Using Machine Learning Collision Cross-Section Prediction and Tandem Mass Spectrometry
| Autor: | Carter K. Asef, Markace A. Rainey, Brianna M. Garcia, Goncalo J. Gouveia, Amanda O. Shaver, Franklin E. Leach, Alison M. Morse, Arthur S. Edison, Lauren M. McIntyre, Facundo M. Fernández |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Analytical Chemistry. |
| ISSN: | 1520-6882 0003-2700 |
| DOI: | 10.1021/acs.analchem.2c03749 |
| Popis: | Ion mobility (IM) spectrometry provides semiorthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics data sets. While current literature has showcased IM-MS for identifying unknowns under near ideal circumstances, less work has been conducted to evaluate the performance of this approach in metabolomics studies involving highly complex samples with difficult matrices. Here, we present a workflow incorporating |
| Databáze: | OpenAIRE |
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