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Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database

Overview of attention for article published in BMC Bioinformatics, July 2011
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters
q&a
1 Q&A thread

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
79 Mendeley
citeulike
7 CiteULike
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Title
Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database
Published in
BMC Bioinformatics, July 2011
DOI 10.1186/1471-2105-12-313
Pubmed ID
Authors

George R Bickerton, Alicia P Higueruelo, Tom L Blundell

Abstract

Structural studies are increasingly providing huge amounts of information on multi-protein assemblies. Although a complete understanding of cellular processes will be dependent on an explicit characterization of the intermolecular interactions that underlie these assemblies and mediate molecular recognition, these are not well described by standard representations.

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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 6%
Spain 3 4%
India 1 1%
Brazil 1 1%
Italy 1 1%
Canada 1 1%
Hungary 1 1%
United States 1 1%
Unknown 65 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 30%
Student > Ph. D. Student 22 28%
Student > Bachelor 7 9%
Student > Master 6 8%
Professor 6 8%
Other 8 10%
Unknown 6 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 46%
Biochemistry, Genetics and Molecular Biology 16 20%
Computer Science 11 14%
Chemistry 4 5%
Engineering 2 3%
Other 3 4%
Unknown 7 9%

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 02 August 2011.
All research outputs
#3,122,277
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#1,406
of 4,576 outputs
Outputs of similar age
#23,575
of 85,807 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 29 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 68% 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 85,807 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 29 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.