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Robustness Can Evolve Gradually in Complex Regulatory Gene Networks with Varying Topology

Overview of attention for article published in PLoS Computational Biology, February 2007
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
4 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
328 Dimensions

Readers on

mendeley
396 Mendeley
citeulike
30 CiteULike
connotea
7 Connotea
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Title
Robustness Can Evolve Gradually in Complex Regulatory Gene Networks with Varying Topology
Published in
PLoS Computational Biology, February 2007
DOI 10.1371/journal.pcbi.0030015
Pubmed ID
Authors

Stefano Ciliberti, Olivier C Martin, Andreas Wagner

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 396 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 5%
Germany 7 2%
Japan 5 1%
Portugal 4 1%
United Kingdom 4 1%
Spain 3 <1%
Norway 2 <1%
Chile 2 <1%
Austria 2 <1%
Other 22 6%
Unknown 326 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 106 27%
Researcher 104 26%
Professor > Associate Professor 38 10%
Student > Bachelor 37 9%
Student > Master 37 9%
Other 60 15%
Unknown 14 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 217 55%
Biochemistry, Genetics and Molecular Biology 53 13%
Computer Science 36 9%
Physics and Astronomy 19 5%
Mathematics 12 3%
Other 30 8%
Unknown 29 7%
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 11 November 2023.
All research outputs
#3,062,928
of 25,877,363 outputs
Outputs from PLoS Computational Biology
#2,662
of 9,063 outputs
Outputs of similar age
#11,651
of 170,650 outputs
Outputs of similar age from PLoS Computational Biology
#3
of 23 outputs
Altmetric has tracked 25,877,363 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 9,063 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. 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 170,650 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 93% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.