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Patterns of Mesenchymal Condensation in a Multiscale, Discrete Stochastic Model

Overview of attention for article published in PLoS Computational Biology, April 2007
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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1 blog
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3 X users

Citations

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70 Dimensions

Readers on

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89 Mendeley
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1 CiteULike
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1 Connotea
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Title
Patterns of Mesenchymal Condensation in a Multiscale, Discrete Stochastic Model
Published in
PLoS Computational Biology, April 2007
DOI 10.1371/journal.pcbi.0030076
Pubmed ID
Authors

Scott Christley, Mark S Alber, Stuart A Newman

Abstract

Cells of the embryonic vertebrate limb in high-density culture undergo chondrogenic pattern formation, which results in the production of regularly spaced "islands" of cartilage similar to the cartilage primordia of the developing limb skeleton. The first step in this process, in vitro and in vivo, is the generation of "cell condensations," in which the precartilage cells become more tightly packed at the sites at which cartilage will form. In this paper we describe a discrete, stochastic model for the behavior of limb bud precartilage mesenchymal cells in vitro. The model uses a biologically motivated reaction-diffusion process and cell-matrix adhesion (haptotaxis) as the bases of chondrogenic pattern formation, whereby the biochemically distinct condensing cells, as well as the size, number, and arrangement of the multicellular condensations, are generated in a self-organizing fashion. Improving on an earlier lattice-gas representation of the same process, it is multiscale (i.e., cell and molecular dynamics occur on distinct scales), and the cells are represented as spatially extended objects that can change their shape. The authors calibrate the model using experimental data and study sensitivity to changes in key parameters. The simulations have disclosed two distinct dynamic regimes for pattern self-organization involving transient or stationary inductive patterns of morphogens. The authors discuss these modes of pattern formation in relation to available experimental evidence for the in vitro system, as well as their implications for understanding limb skeletal patterning during embryonic development.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 2%
Netherlands 1 1%
India 1 1%
United Kingdom 1 1%
Switzerland 1 1%
Spain 1 1%
Canada 1 1%
United States 1 1%
Croatia 1 1%
Other 0 0%
Unknown 79 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 22%
Student > Ph. D. Student 18 20%
Professor > Associate Professor 13 15%
Professor 11 12%
Student > Master 8 9%
Other 12 13%
Unknown 7 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 35%
Biochemistry, Genetics and Molecular Biology 15 17%
Engineering 13 15%
Medicine and Dentistry 6 7%
Materials Science 4 4%
Other 12 13%
Unknown 8 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 13 June 2021.
All research outputs
#2,965,610
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#2,619
of 8,960 outputs
Outputs of similar age
#7,763
of 86,750 outputs
Outputs of similar age from PLoS Computational Biology
#7
of 28 outputs
Altmetric has tracked 25,373,627 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 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 70% 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 86,750 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.