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Computational approaches to protein inference in shotgun proteomics

Overview of attention for article published in BMC Bioinformatics, November 2012
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
1 patent

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
121 Mendeley
citeulike
2 CiteULike
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Title
Computational approaches to protein inference in shotgun proteomics
Published in
BMC Bioinformatics, November 2012
DOI 10.1186/1471-2105-13-s16-s4
Pubmed ID
Authors

Yong Fuga Li, Predrag Radivojac

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 3 2%
Germany 1 <1%
Netherlands 1 <1%
France 1 <1%
Denmark 1 <1%
Sri Lanka 1 <1%
Unknown 110 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 31%
Researcher 28 23%
Student > Master 14 12%
Student > Bachelor 8 7%
Professor > Associate Professor 6 5%
Other 17 14%
Unknown 10 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 32%
Biochemistry, Genetics and Molecular Biology 28 23%
Computer Science 13 11%
Chemistry 6 5%
Medicine and Dentistry 5 4%
Other 16 13%
Unknown 14 12%
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 03 June 2015.
All research outputs
#7,475,808
of 22,854,458 outputs
Outputs from BMC Bioinformatics
#3,026
of 7,292 outputs
Outputs of similar age
#59,303
of 183,608 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 112 outputs
Altmetric has tracked 22,854,458 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,292 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 183,608 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 112 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 50% of its contemporaries.