The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Nonlinear Data Alignment for UPLC−MS and HPLC−MS Based Metabolomics: Quantitative Analysis of Endogenous and Exogenous Metabolites in Human Serum
Open accessAbstract
A nonlinear alignment strategy was examined for the quantitative analysis of serum metabolites. Two small-molecule mixtures with a difference in relative concentration of 20-100% for 10 of the compounds were added to human serum. The metabolomics protocol using UPLC and XCMS for LC-MS data alignment could readily identify 8 of 10 spiked differences among more than 2700 features detected. Normalization of data against a single factor obtained through averaging the XCMS integrated response areas of spiked standards increased the number of identified differences. The original data structure was well preserved using XCMS, but reintegration of identified differences in the original data reduced the number of false positives. Using UPLC for separation resulted in 20% more detected components compared to HPLC. The length of the chromatographic separation also proved to be a crucial parameter for a number of detected features. Moreover, UPLC displayed better retention time reproducibility and signal-to-noise ratios for spiked compounds over HPLC, making this technology more suitable for nontargeted metabolomics applications.
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A Strategy for Identifying Differences in Large Series of Metabolomic Samples Analyzed by GC/MS
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Cited by
Data processing for mass spectrometry-based metabolomics
Katajamaa, M., & Orešič, M. (2007) · Journal of Chromatography A · doi:10.1016/j.chroma.2007.04.021 · Cited by 616
Organization of GC/MS and LC/MS metabolomics data into chemical libraries
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Mass Spectrometry Strategies in Metabolomics
Lei, Z., Huhman, D. V., & Sumner, L. W. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.r111.238691 · Cited by 481
apLCMS—adaptive processing of high-resolution LC/MS data
Yu, T., Park, Y., Johnson, J. M., & Jones, D. P. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp291 · Cited by 406
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Metadata
- Authors
- Nordström, A., O'Maille, G., Qin, C., & Siuzdak, G.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2006-04-11
- Volume
- 78
- Issue
- 10
- Pages
- 3289-3295
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W1978921268
- Cited by
- 273
- References
- 18
- FWCI
- 9.45
- Type
- journal article
- Language
- en
- Open access
- green
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- Nordström, A., O'Maille, G., Qin, C., & Siuzdak, G. (2006). Nonlinear Data Alignment for UPLC−MS and HPLC−MS Based Metabolomics: Quantitative Analysis of Endogenous and Exogenous Metabolites in Human Serum. Analytical Chemistry. https://doi.org/10.1021/ac060245f
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