The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
SIRIUS: decomposing isotope patterns for metabolite identification
Open accessAbstract
Motivation: High-resolution mass spectrometry (MS) is among the most widely used technologies in metabolomics. Metabolites participate in almost all cellular processes, but most metabolites still remain uncharacterized. Determination of the sum formula is a crucial step in the identification of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set. Results: We present a method for determining the sum formula of a metabolite solely from its mass and the natural distribution of its isotopes. Our input is a measured isotope pattern from a high resolution mass spectrometer, and we want to find those molecules that best match this pattern. Our method is computationally efficient, and results on experimental data are very promising: for orthogonal time-of-flight mass spectrometry, we correctly identify sum formulas for >90% of the molecules, ranging in mass up to 1000 Da. Availability: SIRIUS is available under the LGPL license at http://bio.informatik.uni-jena.de/sirius/ Contact: anton.pervukhin@minet.uni-jena.de Supplementary information: Supplementary data are available at Bioinformatics online.
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Kind, T., & Fiehn, O. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-105 · Cited by 1,201
Cited by
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Dührkop, K., Fleischauer, M., Ludwig, M., Aksenov, A. A., Melnik, A. V., Meusel, M., Dorrestein, P. C., Rousu, J., & Böcker, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0344-8 · Cited by 2,060
Self-citationSoftware Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics
Blaženović, I., Kind, T., Ji, J., & Fiehn, O. (2018) · Metabolites · doi:10.3390/metabo8020031 · Cited by 757
Willighagen, E. L., Mayfield, J. W., Alvarsson, J., Berg, A., Carlsson, L., Jeliazkova, N., Kuhn, S., Pluskal, T., Rojas-Chertó, M., Spjuth, O., et al. (2017) · Journal of Cheminformatics · doi:10.1186/s13321-017-0220-4 · Cited by 527
Topic modeling for untargeted substructure exploration in metabolomics
van der Hooft, J. J. J., Wandy, J., Barrett, M. P., Burgess, K. E. V., & Rogers, S. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608041113 · Cited by 365
Propagating annotations of molecular networks using in silico fragmentation
da Silva, R. R., Wang, M., Nothias, L.-F., van der Hooft, J. J. J., Caraballo-Rodríguez, A. M., Fox, E., Balunas, M. J., Klassen, J. L., Lopes, N. P., & Dorrestein, P. C. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006089 · Cited by 363
Metadata
- Authors
- Böcker, S., Letzel, M. C., Lipták, Z., & Pervukhin, A.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-11-17
- Volume
- 25
- Issue
- 2
- Pages
- 218-224
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2150827955
- Cited by
- 354
- References
- 1
- FWCI
- 3.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Böcker, S., Letzel, M. C., Lipták, Z., & Pervukhin, A. (2009). SIRIUS: decomposing isotope patterns for metabolite identification. Bioinformatics. https://doi.org/10.1093/bioinformatics/btn603
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