Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 366

The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.

Advances in Mass Spectrometry for Lipidomics

Blanksby, Stephen J., Mitchell, Todd W.·2010·Annual Review of Analytical Chemistry

Abstract

Recent expansion in research in the field of lipidomics has been driven by the development of new mass spectrometric tools and protocols for the identification and quantification of molecular lipids in complex matrices. Although there are similarities between the field of lipidomics and the allied field of mass spectrometry (e.g., proteomics), lipids present some unique advantages and challenges for mass spectrometric analysis. The application of electrospray ionization to crude lipid extracts without prior fractionation—the so-called shotgun approach—is one such example, as it has perhaps been more successfully applied in lipidomics than in any other discipline. Conversely, the diverse molecular structure of lipids means that collision-induced dissociation alone may be limited in providing unique descriptions of complex lipid structures, and the development of additional, complementary tools for ion activation and analysis is required to overcome these challenges. In this article, we discuss the state of the art in lipid mass spectrometry and highlight several areas in which current approaches are deficient and further innovation is required.

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 · 10.1146/annurev.anchem.111808.073705

Cites

113 of 113 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 113 references

Cited by

See all 366

Metadata

Authors
Blanksby, S. J., & Mitchell, T. W.
Venue
Annual Review of Analytical Chemistry
Published
2010-06-01
Volume
3
Issue
1
Pages
433-465
ISSN
  • 1936-1327 (ISSN-L)
  • 1936-1335
OpenAlex
W2161210686
Cited by
366
References
113
FWCI
1.01
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: Advances in Mass Spectrometry for Lipidomics. https://app.cochat.ai/papers/10.1146/annurev.anchem.111808.073705
The paper
Blanksby, S. J., & Mitchell, T. W. (2010). Advances in Mass Spectrometry for Lipidomics. Annual Review of Analytical Chemistry. https://doi.org/10.1146/annurev.anchem.111808.073705

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.