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Cited by 328

The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.

Membrane curvature in cell biology: An integration of molecular mechanisms

Open access
Jarsch, Iris K., Daste, Frederic, Gallop, Jennifer L.·2016·Journal of Cell Biology

Abstract

Curving biological membranes establishes the complex architecture of the cell and mediates membrane traffic to control flux through subcellular compartments. Common molecular mechanisms for bending membranes are evident in different cell biological contexts across eukaryotic phyla. These mechanisms can be intrinsic to the membrane bilayer (either the lipid or protein components) or can be brought about by extrinsic factors, including the cytoskeleton. Here, we review examples of membrane curvature generation in animals, fungi, and plants. We showcase the molecular mechanisms involved and how they collaborate and go on to highlight contexts of curvature that are exciting areas of future research. Lessons from how membranes are bent in yeast and mammals give hints as to the molecular mechanisms we expect to see used by plants and protists.

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Crossref · 10.1083/jcb.201604003

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Metadata

Authors
Jarsch, I. K., Daste, F., & Gallop, J. L.
Venue
Journal of Cell Biology
Published
2016-08-15
Volume
214
Issue
4
Pages
375-387
ISSN
  • 0021-9525 (ISSN-L)
  • 1540-8140
OpenAlex
W2507465516
Cited by
328
References
117
FWCI
15.50
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Membrane curvature in cell biology: An integration of molecular mechanisms. https://app.cochat.ai/papers/10.1083/jcb.201604003
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Jarsch, I. K., Daste, F., & Gallop, J. L. (2016). Membrane curvature in cell biology: An integration of molecular mechanisms. Journal of Cell Biology. https://doi.org/10.1083/jcb.201604003

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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.