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Network Evolution: Rewiring and Signatures of Conservation in Signaling

Overview of attention for article published in PLoS Computational Biology, March 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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6 X users

Citations

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30 Dimensions

Readers on

mendeley
103 Mendeley
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8 CiteULike
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Title
Network Evolution: Rewiring and Signatures of Conservation in Signaling
Published in
PLoS Computational Biology, March 2012
DOI 10.1371/journal.pcbi.1002411
Pubmed ID
Authors

Mark G. F. Sun, Martin Sikora, Michael Costanzo, Charles Boone, Philip M. Kim

Abstract

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 2%
Canada 2 2%
United Kingdom 2 2%
Chile 1 <1%
Germany 1 <1%
Italy 1 <1%
Australia 1 <1%
Argentina 1 <1%
Denmark 1 <1%
Other 3 3%
Unknown 88 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 33%
Student > Ph. D. Student 29 28%
Professor > Associate Professor 11 11%
Student > Master 6 6%
Professor 5 5%
Other 13 13%
Unknown 5 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 68 66%
Biochemistry, Genetics and Molecular Biology 14 14%
Computer Science 5 5%
Chemistry 2 2%
Medicine and Dentistry 2 2%
Other 5 5%
Unknown 7 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 March 2012.
All research outputs
#7,355,930
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#4,994
of 8,960 outputs
Outputs of similar age
#46,649
of 169,061 outputs
Outputs of similar age from PLoS Computational Biology
#50
of 111 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
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 is in the 43rd percentile – i.e., 43% 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 169,061 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 70% of its contemporaries.
We're also able to compare this research output to 111 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 54% of its contemporaries.