Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 317

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping

van der Kloet, Frans M., Bobeldijk, Ivana, Verheij, Elwin R., Jellema, Renger H.·2009·Journal of Proteome Research

Abstract

Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the analytical data quality without the availability of suitable labeled internal standards and calibration standards even within one laboratory. In this paper, we suggest a workflow for significant reduction of the analytical error using pooled calibration samples and multiple internal standard strategy. Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/pr900499r

Cites

22 of 22 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 22 references

Cited by

See all 317

Metadata

Authors
van der Kloet, F. M., Bobeldijk, I., Verheij, E. R., & Jellema, R. H.
Venue
Journal of Proteome Research
Published
2009-09-30
Volume
8
Issue
11
Pages
5132-5141
ISSN
  • 1535-3893 (ISSN-L)
  • 1535-3907
OpenAlex
W2125575989
Cited by
317
References
22
FWCI
2.88
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: Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping. https://app.cochat.ai/papers/10.1021/pr900499r
The paper
van der Kloet, F. M., Bobeldijk, I., Verheij, E. R., & Jellema, R. H. (2009). Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping. Journal of Proteome Research. https://doi.org/10.1021/pr900499r

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.