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Predicting phenotypic traits of prokaryotes from protein domain frequencies

Overview of attention for article published in BMC Bioinformatics, September 2010
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Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
64 Mendeley
citeulike
2 CiteULike
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Title
Predicting phenotypic traits of prokaryotes from protein domain frequencies
Published in
BMC Bioinformatics, September 2010
DOI 10.1186/1471-2105-11-481
Pubmed ID
Authors

Thomas Lingner, Stefanie Mühlhausen, Toni Gabaldón, Cedric Notredame, Peter Meinicke

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
Brazil 1 2%
Germany 1 2%
Spain 1 2%
United Kingdom 1 2%
Unknown 56 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 33%
Student > Ph. D. Student 14 22%
Student > Master 8 13%
Professor > Associate Professor 6 9%
Student > Bachelor 2 3%
Other 8 13%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 53%
Computer Science 8 13%
Biochemistry, Genetics and Molecular Biology 7 11%
Immunology and Microbiology 4 6%
Chemical Engineering 3 5%
Other 3 5%
Unknown 5 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 May 2016.
All research outputs
#18,459,684
of 22,873,031 outputs
Outputs from BMC Bioinformatics
#6,330
of 7,297 outputs
Outputs of similar age
#87,146
of 97,294 outputs
Outputs of similar age from BMC Bioinformatics
#46
of 52 outputs
Altmetric has tracked 22,873,031 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,297 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 97,294 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.