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Cited by 567

The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.

Curvature, Lipid Packing, and Electrostatics of Membrane Organelles: Defining Cellular Territories in Determining Specificity

Open access
Bigay, Joëlle, Antonny, Bruno·2012·Developmental Cell

Abstract

Whereas some rare lipids contribute to the identity of cell organelles, we focus on the abundant lipids that form the matrix of organelle membranes. Observations using bioprobes and peripheral proteins, notably sensors of membrane curvature, support the prediction that the cell contains two broad membrane territories: the territory of loose lipid packing, where cytosolic proteins take advantage of membrane defects, and the territory of electrostatics, where proteins are attracted by negatively charged lipids. The contrasting features of these territories provide specificity for reactions occurring along the secretory pathway, on the plasma membrane, and also on lipid droplets and autophagosomes.

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Crossref · 10.1016/j.devcel.2012.10.009

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Metadata

Authors
Bigay, J., & Antonny, B.
Venue
Developmental Cell
Publisher
Elsevier BV
Published
2012-11
Volume
23
Issue
5
Pages
886-895
ISSN
1534-5807 (ISSN-L)
OpenAlex
W2046189032
Cited by
567
References
96
FWCI
9.64
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Curvature, Lipid Packing, and Electrostatics of Membrane Organelles: Defining Cellular Territories in Determining Specificity. https://app.cochat.ai/papers/10.1016/j.devcel.2012.10.009
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Bigay, J., & Antonny, B. (2012). Curvature, Lipid Packing, and Electrostatics of Membrane Organelles: Defining Cellular Territories in Determining Specificity. Developmental Cell. https://doi.org/10.1016/j.devcel.2012.10.009

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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.