The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics
Open accessAbstract
The chemical identification of mass spectrometric signals in metabolomic applications is important to provide conversion of analytical data to biological knowledge about metabolic pathways. The complexity of electrospray mass spectrometric data acquired from a range of samples (serum, urine, yeast intracellular extracts, yeast metabolic footprints, placental tissue metabolic footprints) has been investigated and has defined the frequency of different ion types routinely detected. Although some ion types were expected (protonated and deprotonated peaks, isotope peaks, multiply charged peaks) others were not expected (sodium formate adduct ions). In parallel, the Manchester Metabolomics Database (MMD) has been constructed with data from genome scale metabolic reconstructions, HMDB, KEGG, Lipid Maps, BioCyc and DrugBank to provide knowledge on 42,687 endogenous and exogenous metabolite species. The combination of accurate mass data for a large collection of metabolites, theoretical isotope abundance data and knowledge of the different ion types detected provided a greater number of electrospray mass spectrometric signals which were putatively identified and with greater confidence in the samples studied. To provide definitive identification metabolite-specific mass spectral libraries for UPLC-MS and GC-MS have been constructed for 1,065 commercially available authentic standards. The MMD data are available at http://dbkgroup.org/MMD/.
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Caspi, R., Billington, R., Ferrer, L., Foerster, H., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1164 · Cited by 3,395
Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., Blüthgen, N., Borger, S., Costenoble, R., Heinemann, M., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1492 · Cited by 588
Self-citationThe Edinburgh human metabolic network reconstruction and its functional analysis
Ma, H., Sorokin, A., Mazein, A., Selkov, A., Selkov, E., Demin, O., & Goryanin, I. (2007) · Molecular Systems Biology · doi:10.1038/msb4100177 · Cited by 435
Growth control of the eukaryote cell: a systems biology study in yeast
Castrillo, J. I., Zeef, L. A., Hoyle, D. C., Zhang, N., Hayes, A., Gardner, D. C., Cornell, M. J., Petty, J., Hakes, L., Wardleworth, L., et al. (2007) · Journal of Biology · doi:10.1186/jbiol54 · Cited by 263
Self-citationMetabolomics of aquatic organisms: the new omics on the block
Viant, M. (2007) · Marine Ecology Progress Series · doi:10.3354/meps332301 · Cited by 187
Human metabolic network reconstruction and its impact on drug discovery and development
Ma, H., & Goryanin, I. (2008) · Drug Discovery Today · doi:10.1016/j.drudis.2008.02.002 · Cited by 59
Cited by
The Human Serum Metabolome (HUSERMET) Consortium, Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., Brown, M., Knowles, J. D., Halsall, A., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.335 · Cited by 3,294
Self-citationPredicting Network Activity from High Throughput Metabolomics
Li, S., Park, Y., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., Jones, D. P., & Pulendran, B. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003123 · Cited by 936
Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics
Dunn, W. B., Erban, A., Weber, R. J. M., Creek, D. J., Brown, M., Breitling, R., Hankemeier, T., Goodacre, R., Neumann, S., Kopka, J., et al. (2013) · Metabolomics · doi:10.1007/s11306-012-0434-4 · Cited by 555
Self-citationBridgewater BR, E. A. (2014) · Journal of Postgenomics Drug & Biomarker Development · doi:10.4172/2153-0769.1000132 · Cited by 389
Creek, D. J., Jankevics, A., Breitling, R., Watson, D. G., Barrett, M. P., & Burgess, K. E. V. (2011) · Analytical Chemistry · doi:10.1021/ac2021823 · Cited by 344
Metadata
- Authors
- Brown, M., Dunn, W. B., Dobson, P., Patel, Y., Winder, C. L., Francis-McIntyre, S., Begley, P., Carroll, K., Broadhurst, D., Tseng, A., Swainston, N., Spasic, I., Goodacre, R., & Kell, D. B.
- Venue
- The Analyst
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2009
- Volume
- 134
- Issue
- 7
- Pages
- 1322
- ISSN
- 0003-2654 (ISSN-L)
- 1364-5528
- OpenAlex
- W2140181854
- Cited by
- 269
- References
- 6
- FWCI
- 9.48
- Type
- journal article
- Language
- en
- Open access
- green
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- Brown, M., Dunn, W. B., Dobson, P., Patel, Y., Winder, C. L., Francis-McIntyre, S., Begley, P., Carroll, K., Broadhurst, D., Tseng, A., Swainston, N., Spasic, I., Goodacre, R., & Kell, D. B. (2009). Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. The Analyst. https://doi.org/10.1039/b901179j
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