The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Monolithic Silica-Based Capillary Reversed-Phase Liquid Chromatography/Electrospray Mass Spectrometry for Plant Metabolomics
Open accessAbstract
Application of C18 monolithic silica capillary columns in HPLC coupled to ion trap mass spectrometry detection was studied for probing the metabolome of the model plant Arabidopsis thaliana. It could be shown that the use of a long capillary column is an easy and effective approach to reduce ionization suppression by enhanced chromatographic resolution. Several hundred peaks could be detected using a 90-cm capillary column for LC separation and a noise reduction and automatic peak alignment software, which outperformed manual inspection or commercially available mass spectral deconvolution software.
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
Analysis of the genome sequence of the flowering plant Arabidopsis thaliana
Initiative, T. A. G. (2000) · Nature · doi:10.1038/35048692 · Cited by 9,301
Cited by
Lommen, A. (2009) · Analytical Chemistry · doi:10.1021/ac900036d · Cited by 734
Self-citationScalbert, A., Brennan, L., Fiehn, O., Hankemeier, T., Kristal, B. S., van Ommen, B., Pujos-Guillot, E., Verheij, E., Wishart, D., & Wopereis, S. (2009) · Metabolomics · doi:10.1007/s11306-009-0168-0 · Cited by 565
Self-citationMetabolomics 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
LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics
Theodoridis, G., Gika, H. G., & Wilson, I. D. (2008) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2008.01.008 · Cited by 371
MyCompoundID: using an evidence-based metabolome library for metabolite identification
Li, L., Li, R., Zhou, J., Zuniga, A., Stanislaus, A. E., Wu, Y., Huan, T., Zheng, J., Shi, Y., Wishart, D. S., et al. (2013) · Analytical Chemistry · doi:10.1021/ac400099b · Cited by 229
Metadata
- Authors
- Tolstikov, V. V., Lommen, A., Nakanishi, K., Tanaka, N., & Fiehn, O.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-10-28
- Volume
- 75
- Issue
- 23
- Pages
- 6737-6740
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2088185375
- Cited by
- 260
- References
- 1
- FWCI
- 7.51
- Type
- journal article
- Language
- en
- Open access
- green
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
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.
