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Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

Overview of attention for article published in PLoS Computational Biology, August 2010
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Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
89 Mendeley
citeulike
3 CiteULike
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Title
Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors
Published in
PLoS Computational Biology, August 2010
DOI 10.1371/journal.pcbi.1000908
Pubmed ID
Authors

Thomas C. Whisenant, David T. Ho, Ryan W. Benz, Jeffrey S. Rogers, Robyn M. Kaake, Elizabeth A. Gordon, Lan Huang, Pierre Baldi, Lee Bardwell

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
United States 2 2%
Argentina 1 1%
Hungary 1 1%
Russia 1 1%
China 1 1%
Unknown 81 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 30%
Researcher 12 13%
Student > Bachelor 9 10%
Professor > Associate Professor 7 8%
Student > Master 7 8%
Other 21 24%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 49%
Biochemistry, Genetics and Molecular Biology 16 18%
Medicine and Dentistry 9 10%
Computer Science 3 3%
Physics and Astronomy 2 2%
Other 7 8%
Unknown 8 9%
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 18 May 2017.
All research outputs
#8,534,528
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#5,636
of 8,960 outputs
Outputs of similar age
#38,035
of 103,402 outputs
Outputs of similar age from PLoS Computational Biology
#33
of 59 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
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 33rd percentile – i.e., 33% 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 103,402 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.