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SimBA: A methodology and tools for evaluating the performance of RNA-Seq bioinformatic pipelines

Overview of attention for article published in BMC Bioinformatics, September 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
48 Mendeley
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Title
SimBA: A methodology and tools for evaluating the performance of RNA-Seq bioinformatic pipelines
Published in
BMC Bioinformatics, September 2017
DOI 10.1186/s12859-017-1831-5
Pubmed ID
Authors

Jérôme Audoux, Mikaël Salson, Christophe F. Grosset, Sacha Beaumeunier, Jean-Marc Holder, Thérèse Commes, Nicolas Philippe

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 23%
Researcher 8 17%
Student > Bachelor 7 15%
Student > Master 4 8%
Other 3 6%
Other 8 17%
Unknown 7 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 31%
Agricultural and Biological Sciences 13 27%
Engineering 4 8%
Computer Science 3 6%
Medicine and Dentistry 2 4%
Other 2 4%
Unknown 9 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 01 June 2019.
All research outputs
#5,990,843
of 23,149,216 outputs
Outputs from BMC Bioinformatics
#2,194
of 7,339 outputs
Outputs of similar age
#95,309
of 321,383 outputs
Outputs of similar age from BMC Bioinformatics
#32
of 100 outputs
Altmetric has tracked 23,149,216 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,339 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 69% 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 321,383 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 100 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 68% of its contemporaries.