The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Targeted Metabolomics for Biomarker Discovery
Abstract
Metabolomics is a truly interdisciplinary field of science, which combines analytical chemistry, platform technology, mass spectrometry, and NMR spectroscopy with sophisticated data analysis. Applied to biomarker discovery, it includes aspects of pathobiochemistry, systems biology/medicine, and molecular diagnostics and requires bioinformatics and multivariate statistics. While successfully established in the screening of inborn errors in neonates, metabolomics is now widely used in the characterization and diagnostic research of an ever increasing number of diseases. In this Review we highlight important technical prerequisites as well as recent developments in metabolomics and metabolomics data analysis with special emphasis on their utility in biomarker identification and qualification, as well as targeted metabolomics by employing high‐throughput mass spectrometry.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bias in error estimation when using cross-validation for model selection
Varma, S., & Simon, R. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-91 · Cited by 2,485
van den Berg, R. A., Hoefsloot, H. C., Westerhuis, J. A., Smilde, A. K., & van der Werf, M. J. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-142 · Cited by 2,450
Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440
Activation of the Nuclear Receptor LXR by Oxysterols Defines a New Hormone Response Pathway
Lehmann, J. M., Kliewer, S. A., Moore, L. B., Smith-Oliver, T. A., Oliver, B. B., Su, J.-L., Sundseth, S. S., Winegar, D. A., Blanchard, D. E., Spencer, T. A., et al. (1997) · Journal of Biological Chemistry · doi:10.1074/jbc.272.6.3137 · Cited by 1,233
Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum
Gieger, C., Geistlinger, L., Altmaier, E., Hrabé de Angelis, M., Kronenberg, F., Meitinger, T., Mewes, H.-W., Wichmann, H.-E., Weinberger, K. M., Adamski, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000282 · Cited by 737
Bile acids as regulatory molecules
Hylemon, P. B., Zhou, H., Pandak, W. M., Ren, S., Gil, G., & Dent, P. (2009) · Journal of Lipid Research · doi:10.1194/jlr.r900007-jlr200 · Cited by 694
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
Björkhem, I., Lütjohann, D., Diczfalusy, U., Ståhle, L., Ahlborg, G., & Wahren, J. (1998) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)32188-x · Cited by 538
Metabolomics and systems biology: making sense of the soup
KELL, D. (2004) · Current Opinion in Microbiology · doi:10.1016/j.mib.2004.04.012 · Cited by 529
Setchell, K. D., Schwarz, M., O'Connell, N. C., Lund, E. G., Davis, D. L., Lathe, R., Thompson, H. R., Weslie Tyson, R., Sokol, R. J., & Russell, D. W. (1998) · Journal of Clinical Investigation · doi:10.1172/jci2962 · Cited by 375
Cited by
Zhou, B., Xiao, J. F., Tuli, L., & Ressom, H. W. (2011) · Molecular BioSystems · doi:10.1039/c1mb05350g · Cited by 639
Metabolite identification and quantitation in LC-MS/MS-based metabolomics
Xiao, J. F., Zhou, B., & Ressom, H. W. (2012) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2011.08.009 · Cited by 620
Mass spectrometric based approaches in urine metabolomics and biomarker discovery
Khamis, M. M., Adamko, D. J., & El‐Aneed, A. (2017) · Mass Spectrometry Reviews · doi:10.1002/mas.21455 · Cited by 342
Botticelli, A., Vernocchi, P., Marini, F., Quagliariello, A., Cerbelli, B., Reddel, S., Del Chierico, F., Di Pietro, F., Giusti, R., Tomassini, A., et al. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02231-0 · Cited by 209
Biomarkers intersect with the exposome
Rappaport, S. M. (2012) · Biomarkers · doi:10.3109/1354750x.2012.691553 · Cited by 114
Metadata
- Authors
- Griffiths, W. J., Koal, T., Wang, Y., Kohl, M., Enot, D. P., & Deigner, H.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2010-07-22
- Volume
- 49
- Issue
- 32
- Pages
- 5426-5445
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2006691834
- Cited by
- 415
- References
- 13
- FWCI
- 8.74
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Targeted Metabolomics for Biomarker Discovery. https://app.cochat.ai/papers/10.1002/anie.200905579
- The paper
- Griffiths, W. J., Koal, T., Wang, Y., Kohl, M., Enot, D. P., & Deigner, H. (2010). Targeted Metabolomics for Biomarker Discovery. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200905579
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.