The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites
Open accessAbstract
SUMMARY When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomic method. We first group multiple features arising from the same analyte, which we call “degenerate features”, using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ~2,961. We then applied an orthogonal approach to remove non-biological features from the data by using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1,000.
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Metabolomics: the apogee of the omics trilogy
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Self-citationCurrent Protocols in Molecular Biology
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Emerging applications of metabolomics in drug discovery and precision medicine
Wishart, D. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.32 · Cited by 1,488
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The Syntenic Relationship of the Zebrafish and Human Genomes
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High-confidence structural annotation of metabolites absent from spectral libraries
Hoffmann, M. A., Nothias, L.-F., Ludwig, M., Fleischauer, M., Gentry, E. C., Witting, M., Dorrestein, P. C., Dührkop, K., & Böcker, S. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01045-9 · Cited by 388
A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms
Tsugawa, H., Nakabayashi, R., Mori, T., Yamada, Y., Takahashi, M., Rai, A., Sugiyama, R., Yamamoto, H., Nakaya, T., Yamazaki, M., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0358-2 · Cited by 299
Peter, K. T., Tian, Z., Wu, C., Lin, P., White, S., Du, B., McIntyre, J. K., Scholz, N. L., & Kolodziej, E. P. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b03287 · Cited by 254
Metadata
- Authors
- Mahieu, N. G., & Patti, G. J.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-09-15
- Volume
- 89
- Issue
- 19
- Pages
- 10397-10406
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2725788675
- Cited by
- 320
- References
- 44
- FWCI
- 12.81
- Type
- journal article
- Language
- en
- Open access
- green
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- Mahieu, N. G., & Patti, G. J. (2017). Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites. Analytical Chemistry. https://doi.org/10.1021/acs.analchem.7b02380
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