Abstract
Untargeted mass spectrometry metabolomics studies rely on accurate databases for the identification of metabolic features. Leveraging unique fragmentation patterns as well as characteristic dissociation routes allows for structural information to be gained for specific metabolites and molecular classes, respectively. Here we describe the evolution of METLIN as a resource for small molecule analysis as well as the tools (e.g., Fragment Similarity Search and Neutral Loss Search) used to query the database and their workflows for the identification of molecular entities. Additionally, we will discuss the functionalities of isoMETLIN, a database of isotopic metabolites, and the latest addition to the METLIN family, METLIN-MRM, which facilitates the analysis of quantitative mass spectrometry data generated with triple quadrupole instrumentation.
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Acknowledgments
This research was partially funded by National Institutes of Health grants R35 GM130385, P30 MH062261, P01 DA026146 and U01 CA235493; and by Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory for the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, under contract number DE-AC02-05CH11231. This research benefited from the use of credits from the National Institutes of Health (NIH) Cloud Credits Model Pilot, a component of the NIH Big Data to Knowledge (BD2K) program.
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Montenegro-Burke, J.R., Guijas, C., Siuzdak, G. (2020). METLIN: A Tandem Mass Spectral Library of Standards. In: Li, S. (eds) Computational Methods and Data Analysis for Metabolomics. Methods in Molecular Biology, vol 2104. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0239-3_9
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DOI: https://doi.org/10.1007/978-1-0716-0239-3_9
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