The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Topic modeling for untargeted substructure exploration in metabolomics
Open accessAbstract
Significance: Tandem MS is a technique for compound identification in untargeted metabolomics experiments. Because of a lack of reference spectra, most molecules cannot be identified, and many spectra cannot be used. We present MS2LDA, an unsupervised method (inspired by text-mining) that extracts common patterns of mass fragments and neutral losses—Mass2Motifs—from collections of fragmentation spectra. Structurally characterized Mass2Motifs can be used to annotate molecules for which no reference spectra exist and expose biochemical relationships between molecules. For four beer extracts, without training data, we show that, with 30 structurally characterized Mass2Motifs, we can annotate approximately three times as many molecules as with library matching. These Mass2Motifs were validated in reference spectra from Global Natural Products Social Molecular Networking (GNPS) and MassBank.
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MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis
Tsugawa, H., Cajka, T., Kind, T., Ma, Y., Higgins, B., Ikeda, K., Kanazawa, M., VanderGheynst, J., Fiehn, O., & Arita, M. (2015) · Nature Methods · doi:10.1038/nmeth.3393 · Cited by 3,397
HMDB 3.0—The Human Metabolome Database in 2013
Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., Djoumbou, Y., Mandal, R., Aziat, F., Dong, E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1065 · Cited by 2,845
MassBank: a public repository for sharing mass spectral data for life sciences
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Advances in Neural Information Processing Systems 21
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LDAvis: A method for visualizing and interpreting topics
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Online Learning for Latent Dirichlet Allocation
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Cited by
Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra
Dührkop, K., Nothias, L.-F., Fleischauer, M., Reher, R., Ludwig, M., Hoffmann, M. A., Petras, D., Gerwick, W. H., Rousu, J., Dorrestein, P. C., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0740-8 · Cited by 860
MSNovelist: de novo structure generation from mass spectra
Stravs, M. A., Dührkop, K., Böcker, S., & Zamboni, N. (2022) · Nature Methods · doi:10.1038/s41592-022-01486-3 · Cited by 226
Perez De Souza, L., Alseekh, S., Brotman, Y., & Fernie, A. R. (2020) · Expert Review of Proteomics · doi:10.1080/14789450.2020.1766975 · Cited by 145
Metadata
- Authors
- van der Hooft, J. J. J., Wandy, J., Barrett, M. P., Burgess, K. E. V., & Rogers, S.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2016-11-16
- Volume
- 113
- Issue
- 48
- Pages
- 13738-13743
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2551876238
- Cited by
- 365
- References
- 38
- FWCI
- 9.93
- Type
- journal article
- Language
- en
- Open access
- green
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- van der Hooft, J. J. J., Wandy, J., Barrett, M. P., Burgess, K. E. V., & Rogers, S. (2016). Topic modeling for untargeted substructure exploration in metabolomics. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1608041113
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