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Comparative study of non-invasive force and stress inference methods in tissue

Overview of attention for article published in The European Physical Journal E, April 2013
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Title
Comparative study of non-invasive force and stress inference methods in tissue
Published in
The European Physical Journal E, April 2013
DOI 10.1140/epje/i2013-13045-8
Pubmed ID
Authors

S. Ishihara, K. Sugimura, S. J. Cox, I. Bonnet, Y. Bellaïche, F. Graner

Abstract

In the course of animal development, the shape of tissue emerges in part from mechanical and biochemical interactions between cells. Measuring stress in tissue is essential for studying morphogenesis and its physical constraints. For that purpose, a possible new approach is force inference (up to a single prefactor) from cell shapes and connectivity. It is non-invasive and can provide space-time maps of stress in a whole tissue, unlike existing methods. To validate this approach, three force-inference methods, which differ in their approach of treating indefiniteness in an inverse problem between cell shapes and forces, were compared. Tests using two artificial and two experimental data sets consistently indicate that our Bayesian force inference, by which cell-junction tensions and cell pressures are simultaneously estimated, performs best in terms of accuracy and robustness. Moreover, by measuring the stress anisotropy and relaxation, we cross-validated the force inference and the global annular ablation of tissue, each of which relies on different prefactors. A practical choice of force-inference methods in different systems of interest is discussed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
France 1 <1%
Germany 1 <1%
Japan 1 <1%
United Kingdom 1 <1%
Unknown 98 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 28%
Researcher 26 25%
Student > Doctoral Student 7 7%
Professor > Associate Professor 7 7%
Student > Master 7 7%
Other 14 13%
Unknown 14 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 30%
Physics and Astronomy 24 23%
Biochemistry, Genetics and Molecular Biology 16 15%
Engineering 6 6%
Mathematics 4 4%
Other 6 6%
Unknown 17 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 07 October 2013.
All research outputs
#19,015,492
of 23,577,654 outputs
Outputs from The European Physical Journal E
#490
of 651 outputs
Outputs of similar age
#147,769
of 195,668 outputs
Outputs of similar age from The European Physical Journal E
#6
of 9 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 651 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 195,668 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.