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Methods for visual mining of genomic and proteomic data atlases

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

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

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10 X users

Citations

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Readers on

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85 Mendeley
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9 CiteULike
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Title
Methods for visual mining of genomic and proteomic data atlases
Published in
BMC Bioinformatics, April 2012
DOI 10.1186/1471-2105-13-58
Pubmed ID
Authors

John Boyle, Richard Kreisberg, Ryan Bressler, Sarah Killcoyne

Abstract

As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data. The challenge addressing bioinformatics researches is how to apply this knowledge to data sets that are continually growing in a field that is rapidly changing.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 6%
South Africa 3 4%
United Kingdom 2 2%
Australia 1 1%
Brazil 1 1%
Finland 1 1%
Canada 1 1%
Germany 1 1%
Russia 1 1%
Other 3 4%
Unknown 66 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 35%
Student > Ph. D. Student 15 18%
Student > Master 13 15%
Other 6 7%
Student > Bachelor 5 6%
Other 11 13%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 40%
Computer Science 20 24%
Biochemistry, Genetics and Molecular Biology 9 11%
Medicine and Dentistry 4 5%
Business, Management and Accounting 2 2%
Other 10 12%
Unknown 6 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 04 October 2012.
All research outputs
#4,079,964
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,503
of 7,400 outputs
Outputs of similar age
#27,070
of 164,553 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 103 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 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 done well, scoring higher than 79% 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 164,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 103 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 73% of its contemporaries.