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Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case

Overview of attention for article published in BMC Bioinformatics, February 2015
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Mentioned by

twitter
1 tweeter

Citations

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6 Dimensions

Readers on

mendeley
18 Mendeley
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Title
Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case
Published in
BMC Bioinformatics, February 2015
DOI 10.1186/1471-2105-16-s4-s2
Pubmed ID
Authors

Dusan Popovic, Alejandro Sifrim, Jesse Davis, Yves Moreau, Bart De Moor

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

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 50%
Student > Master 4 22%
Student > Ph. D. Student 4 22%
Student > Bachelor 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 33%
Biochemistry, Genetics and Molecular Biology 5 28%
Mathematics 2 11%
Computer Science 2 11%
Physics and Astronomy 1 6%
Other 2 11%

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 13 May 2015.
All research outputs
#10,995,645
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#4,227
of 4,588 outputs
Outputs of similar age
#189,108
of 227,823 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 2 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% 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 227,823 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.