The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Metabolite identification and quantitation in LC-MS/MS-based metabolomics
Open accessAbstract
Metabolomics aims at detection and quantitation of all metabolites in biological samples. The presence of metabolites with a wide variety of physicochemical properties and different levels of abundance challenges existing analytical platforms used for identification and quantitation of metabolites. Significant efforts have been made to improve analytical and computational methods for metabolomics studies. This review focuses on the use of liquid chromatography with tandem mass spectrometry (LC-MS/MS) for quantitative and qualitative metabolomics studies. It illustrates recent developments in computational methods for metabolite identification, including ion annotation, spectral interpretation and spectral matching. We also review selected reaction monitoring and high-resolution MS for metabolite quantitation. We discuss current challenges in metabolite identification and quantitation as well as potential solutions.
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MassBank: a public repository for sharing mass spectral data for life sciences
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METLIN—a metabolite mass spectral database
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HMDB: a knowledgebase for the human metabolome
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Systematic functional analysis of the yeast genome
Oliver, S. (1998) · Trends in Biotechnology · doi:10.1016/s0167-7799(98)01214-1 · Cited by 1,302
Metabolomics: Current analytical platforms and methodologies
(2005) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2004.11.021 · Cited by 1,192
Metabolomics for Functional Genomics, Systems Biology, and Biotechnology
Saito, K., & Matsuda, F. (2010) · Annual Review of Plant Biology · doi:10.1146/annurev.arplant.043008.092035 · Cited by 744
Krauss, M., Singer, H., & Hollender, J. (2010) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-010-3608-9 · Cited by 743
In silico fragmentation for computer assisted identification of metabolite mass spectra
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Cited by
Current and future perspectives of functional metabolomics in disease studies–A review
Yan, M., & Xu, G. (2018) · Analytica Chimica Acta · doi:10.1016/j.aca.2018.04.006 · Cited by 105
Hu, L., Liu, J., Zhang, W., Wang, T., Zhang, N., Lee, Y. H., & Lu, H. (2020) · Mass Spectrometry Reviews · doi:10.1002/mas.21611 · Cited by 81
Structural elucidation of low abundant metabolites in complex sample matrices
van der Hooft, J. J. J., de Vos, R. C. H., Ridder, L., Vervoort, J., & Bino, R. J. (2013) · Metabolomics · doi:10.1007/s11306-013-0519-8 · Cited by 46
A site-specific map of the human plasma glycome and its age and gender-associated alterations
Merleev, A. A., Park, D., Xie, Y., Kailemia, M. J., Xu, G., Ruhaak, L. R., Kim, K., Hong, Q., Li, Q., Patel, F., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-73588-x · Cited by 17
Metadata
- Authors
- Xiao, J. F., Zhou, B., & Ressom, H. W.
- Venue
- TrAC Trends in Analytical Chemistry
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 32
- Pages
- 1-14
- ISSN
- 0165-9936 (ISSN-L)
- OpenAlex
- W2001265990
- Cited by
- 620
- References
- 61
- FWCI
- 7.29
- Type
- journal article
- Language
- en
- Open access
- green
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- Xiao, J. F., Zhou, B., & Ressom, H. W. (2012). Metabolite identification and quantitation in LC-MS/MS-based metabolomics. TrAC Trends in Analytical Chemistry. https://doi.org/10.1016/j.trac.2011.08.009
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
