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Branch Mode Selection during Early Lung Development

Overview of attention for article published in PLoS Computational Biology, February 2012
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Title
Branch Mode Selection during Early Lung Development
Published in
PLoS Computational Biology, February 2012
DOI 10.1371/journal.pcbi.1002377
Pubmed ID
Authors

Denis Menshykau, Conradin Kraemer, Dagmar Iber

Abstract

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Unknown 89 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 22%
Researcher 17 18%
Student > Bachelor 11 12%
Student > Master 11 12%
Professor > Associate Professor 9 10%
Other 12 13%
Unknown 12 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 33%
Biochemistry, Genetics and Molecular Biology 14 15%
Medicine and Dentistry 7 8%
Mathematics 6 7%
Physics and Astronomy 6 7%
Other 16 17%
Unknown 13 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 March 2012.
All research outputs
#16,784,715
of 25,461,852 outputs
Outputs from PLoS Computational Biology
#7,233
of 8,981 outputs
Outputs of similar age
#107,500
of 167,989 outputs
Outputs of similar age from PLoS Computational Biology
#78
of 116 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 16th percentile – i.e., 16% 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 167,989 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.