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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

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11 Dimensions

Readers on

mendeley
56 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 7%
Brazil 1 2%
Germany 1 2%
Spain 1 2%
United Kingdom 1 2%
Unknown 48 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 32%
Student > Ph. D. Student 14 25%
Student > Master 7 13%
Professor > Associate Professor 6 11%
Other 2 4%
Other 4 7%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 59%
Computer Science 8 14%
Biochemistry, Genetics and Molecular Biology 4 7%
Immunology and Microbiology 4 7%
Social Sciences 1 2%
Other 1 2%
Unknown 5 9%

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
#9,906,139
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,817
of 4,576 outputs
Outputs of similar age
#188,158
of 270,115 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 23 outputs
Altmetric has tracked 12,373,386 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 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% 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 270,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.