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The biophysical nature of cells: potential cell behaviours revealed by analytical and computational studies of cell surface mechanics

Overview of attention for article published in BMC Biophysics, May 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters

Citations

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59 Dimensions

Readers on

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98 Mendeley
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Title
The biophysical nature of cells: potential cell behaviours revealed by analytical and computational studies of cell surface mechanics
Published in
BMC Biophysics, May 2015
DOI 10.1186/s13628-015-0022-x
Pubmed ID
Authors

Ramiro Magno, Verônica A Grieneisen, Athanasius FM Marée

Abstract

The biophysical characteristics of cells determine their shape in isolation and when packed within tissues. Cells can form regular or irregular epithelial structures, round up and form clusters, or deform and attach to substrates. The acquired shape of cells and tissues is a consequence of (i) internal cytoskeletal processes, such as actin polymerisation and cortical myosin contraction, (ii) adhesion molecules within the cell membrane that interact with substrates and neighbouring cells, and (iii) processes that regulate cell volume. Although these processes seem relatively simple, when combined they unleash a rich variety of cellular behaviour that is not readily understandable outside a theoretical framework. We perform a mathematical analysis of a commonly used class of model formalisms that describe cell surface mechanics using an energy-based approach. Predictions are then confirmed through comparison with the computational outcomes of a Vertex model and 2D and 3D simulations of the Cellular Potts model. The analytical study reveals the complete possible spectrum of single cell behaviour and tissue packing in both 2D and 3D, by taking the typical core elements of cell surface mechanics into account: adhesion, cortical tension and volume conservation. We show that from an energy-based description, forces and tensions can be derived, as well as the prediction of cell behaviour and tissue packing, providing an intuitive and biologically relevant mapping between modelling parameters and experiments. The quantitative cellular behaviours and biological insights agree between the analytical study and the diverse computational model formalisms, including the Cellular Potts model. This illustrates the generality of energy-based approaches for cell surface mechanics and highlights how meaningful and quantitative comparisons between models can be established. Moreover, the mathematical analysis reveals direct links between known biophysical properties and specific parameter settings within the Cellular Potts model.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 1%
Netherlands 1 1%
France 1 1%
United Kingdom 1 1%
Spain 1 1%
United States 1 1%
Unknown 92 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 32%
Researcher 18 18%
Student > Master 11 11%
Professor > Associate Professor 6 6%
Student > Doctoral Student 4 4%
Other 13 13%
Unknown 15 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 20%
Physics and Astronomy 16 16%
Engineering 12 12%
Biochemistry, Genetics and Molecular Biology 10 10%
Mathematics 9 9%
Other 14 14%
Unknown 17 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 September 2019.
All research outputs
#1,785,842
of 15,764,869 outputs
Outputs from BMC Biophysics
#6
of 66 outputs
Outputs of similar age
#32,376
of 238,176 outputs
Outputs of similar age from BMC Biophysics
#1
of 1 outputs
Altmetric has tracked 15,764,869 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 66 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 238,176 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them