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Predicting a small molecule-kinase interaction map: A machine learning approach

Overview of attention for article published in Journal of Cheminformatics, June 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

twitter
2 tweeters
patent
1 patent

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
42 Mendeley
citeulike
2 CiteULike
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Title
Predicting a small molecule-kinase interaction map: A machine learning approach
Published in
Journal of Cheminformatics, June 2011
DOI 10.1186/1758-2946-3-22
Pubmed ID
Authors

Fabian Buchwald, Lothar Richter, Stefan Kramer

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Russia 1 2%
Unknown 40 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 24%
Student > Ph. D. Student 9 21%
Student > Master 6 14%
Other 4 10%
Student > Postgraduate 3 7%
Other 6 14%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 24%
Chemistry 9 21%
Computer Science 8 19%
Biochemistry, Genetics and Molecular Biology 2 5%
Medicine and Dentistry 2 5%
Other 6 14%
Unknown 5 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 06 January 2022.
All research outputs
#5,495,610
of 21,479,159 outputs
Outputs from Journal of Cheminformatics
#468
of 788 outputs
Outputs of similar age
#106,799
of 329,417 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 21,479,159 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 788 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 40th percentile – i.e., 40% 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 329,417 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 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them