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Classification of transient behaviours in a time-dependent toggle switch model

Overview of attention for article published in BMC Systems Biology, April 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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11 X users

Citations

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79 Dimensions

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115 Mendeley
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Title
Classification of transient behaviours in a time-dependent toggle switch model
Published in
BMC Systems Biology, April 2014
DOI 10.1186/1752-0509-8-43
Pubmed ID
Authors

Berta Verd, Anton Crombach, Johannes Jaeger

Abstract

Waddington's epigenetic landscape is an intuitive metaphor for the developmental and evolutionary potential of biological regulatory processes. It emphasises time-dependence and transient behaviour. Nowadays, we can derive this landscape by modelling a specific regulatory network as a dynamical system and calculating its so-called potential surface. In this sense, potential surfaces are the mathematical equivalent of the Waddingtonian landscape metaphor. In order to fully capture the time-dependent (non-autonomous) transient behaviour of biological processes, we must be able to characterise potential landscapes and how they change over time. However, currently available mathematical tools focus on the asymptotic (steady-state) behaviour of autonomous dynamical systems, which restricts how biological systems are studied.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
Portugal 1 <1%
United Kingdom 1 <1%
Denmark 1 <1%
China 1 <1%
Spain 1 <1%
Unknown 107 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 31%
Researcher 27 23%
Student > Bachelor 12 10%
Student > Master 9 8%
Professor > Associate Professor 6 5%
Other 10 9%
Unknown 15 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 36%
Biochemistry, Genetics and Molecular Biology 25 22%
Physics and Astronomy 8 7%
Mathematics 6 5%
Computer Science 4 3%
Other 15 13%
Unknown 16 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 22 May 2022.
All research outputs
#5,810,825
of 23,342,092 outputs
Outputs from BMC Systems Biology
#186
of 1,143 outputs
Outputs of similar age
#53,863
of 227,506 outputs
Outputs of similar age from BMC Systems Biology
#3
of 24 outputs
Altmetric has tracked 23,342,092 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,143 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 83% 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 227,506 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 76% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.