Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 196

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

Giant vesicles as cell models

Fenz, Susanne F., Sengupta, Kheya·2012·Integrative Biology

Abstract

Tremendous progress has been made in recent years in understanding the working of the living cell, including its micro-anatomy, signalling networks, and regulation of genes. However, an understanding of cellular phenomena using fundamental laws starting from first principles is still very far away. Part of the reason is that a cell is an active and exquisitely complex system where every part is linked to the other. Thus, it is difficult or even impossible to design experiments that selectively and exclusively probe a chosen aspect of the cell. Various kinds of idealised systems and cell models have been used to circumvent this problem. An important example is a giant unilamellar vesicle (GUV, also called giant liposome), which provides a cell-sized confined volume to study biochemical reactions as well as self-assembly processes that occur on the membrane. The GUV membrane can be designed suitably to present selected, correctly-oriented cell-membrane proteins, whose mobility is confined to two dimensions. Here, we present recent advances in GUV design and the use of GUVs as cell models that enable quantitative testing leading to insight into the working of real cells. We briefly recapitulate important classical concepts in membrane biophysics emphasising the advantages and limitations of GUVs. We then present results obtained over the last decades using GUVs, choosing the formation of membrane domains and cell adhesion as examples for in-depth treatment. Insight into cell adhesion obtained using micro-interferometry is treated in detail. We conclude by summarising the open questions and possible future directions.

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 · 10.1039/c2ib00188h

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 196

Metadata

Authors
Fenz, S. F., & Sengupta, K.
Venue
Integrative Biology
Published
2012
Volume
4
Issue
9
Pages
982
ISSN
  • 1757-9694 (ISSN-L)
  • 1757-9708
OpenAlex
W2051953600
Cited by
196
References
5
FWCI
4.18
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: Giant vesicles as cell models. https://app.cochat.ai/papers/10.1039/c2ib00188h
The paper
Fenz, S. F., & Sengupta, K. (2012). Giant vesicles as cell models. Integrative Biology. https://doi.org/10.1039/c2ib00188h

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.