Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 661

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Single-Cell Metabolomics: Analytical and Biological Perspectives

Zenobi, R.·2013·Science

Abstract

There is currently much interest in broad molecular profiling of single cells; a cell’s metabolome—its full complement of small-molecule metabolites—is a direct indicator of phenotypic diversity of single cells and a nearly immediate readout of how cells react to environmental influences. However, the metabolome is very difficult to measure at the single-cell level because of rapid metabolic dynamics, the structural diversity of the molecules, and the inability to amplify or tag small-molecule metabolites. Measurement techniques including mass spectrometry, capillary electrophoresis, and, to a lesser extent, optical spectroscopy and fluorescence detection have led to impressive advances in single-cell metabolomics. Even though none of these methodologies can currently measure the metabolome of a single cell completely, rapidly, and nondestructively, progress has been sufficient such that the field is witnessing a shift from feasibility studies to investigations that yield new biological insight. Particularly interesting fields of application are cancer biology, stem cell research, and monitoring of xenobiotics and drugs in tissue sections at the single-cell level.

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 · 10.1126/science.1243259

Cites

5 of 5 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 5 references

Cited by

See all 661

Metadata

Authors
Zenobi, R.
Venue
Science
Published
2013-12-06
Volume
342
Issue
6163
Pages
1243259-1243259
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2100542429
Cited by
661
References
5
FWCI
17.08
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: Single-Cell Metabolomics: Analytical and Biological Perspectives. https://app.cochat.ai/papers/10.1126/science.1243259
The paper
Zenobi, R. (2013). Single-Cell Metabolomics: Analytical and Biological Perspectives. Science. https://doi.org/10.1126/science.1243259

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.