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A model of the regulatory network involved in the control of the cell cycle and cell differentiation in the Caenorhabditis elegans vulva

Overview of attention for article published in BMC Bioinformatics, March 2015
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
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7 X users
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Citations

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9 Dimensions

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47 Mendeley
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1 CiteULike
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Title
A model of the regulatory network involved in the control of the cell cycle and cell differentiation in the Caenorhabditis elegans vulva
Published in
BMC Bioinformatics, March 2015
DOI 10.1186/s12859-015-0498-z
Pubmed ID
Authors

Nathan Weinstein, Elizabeth Ortiz-Gutiérrez, Stalin Muñoz, David A Rosenblueth, Elena R Álvarez-Buylla, Luis Mendoza

Abstract

There are recent experimental reports on the cross-regulation between molecules involved in the control of the cell cycle and the differentiation of the vulval precursor cells (VPCs) of Caenorhabditis elegans. Such discoveries provide novel clues on how the molecular mechanisms involved in the cell cycle and cell differentiation processes are coordinated during vulval development. Dynamic computational models are helpful to understand the integrated regulatory mechanisms affecting these cellular processes. Here we propose a simplified model of the regulatory network that includes sufficient molecules involved in the control of both the cell cycle and cell differentiation in the C. elegans vulva to recover their dynamic behavior. We first infer both the topology and the update rules of the cell cycle module from an expected time series. Next, we use a symbolic algorithmic approach to find which interactions must be included in the regulatory network. Finally, we use a continuous-time version of the update rules for the cell cycle module to validate the cyclic behavior of the network, as well as to rule out the presence of potential artifacts due to the synchronous updating of the discrete model. We analyze the dynamical behavior of the model for the wild type and several mutants, finding that most of the results are consistent with published experimental results. Our model shows that the regulation of Notch signaling by the cell cycle preserves the potential of the VPCs and the three vulval fates to differentiate and de-differentiate, allowing them to remain completely responsive to the concentration of LIN-3 and lateral signal in the extracellular microenvironment.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 2%
Brazil 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 36%
Researcher 9 19%
Student > Bachelor 6 13%
Professor > Associate Professor 3 6%
Student > Master 3 6%
Other 8 17%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 40%
Biochemistry, Genetics and Molecular Biology 13 28%
Mathematics 3 6%
Computer Science 2 4%
Social Sciences 2 4%
Other 5 11%
Unknown 3 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 August 2015.
All research outputs
#12,919,128
of 22,794,367 outputs
Outputs from BMC Bioinformatics
#3,786
of 7,281 outputs
Outputs of similar age
#118,839
of 260,871 outputs
Outputs of similar age from BMC Bioinformatics
#69
of 146 outputs
Altmetric has tracked 22,794,367 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,281 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 45th percentile – i.e., 45% 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 260,871 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.