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GEOlimma: differential expression analysis and feature selection using pre-existing microarray data

Overview of attention for article published in BMC Bioinformatics, February 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
32 Mendeley
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Title
GEOlimma: differential expression analysis and feature selection using pre-existing microarray data
Published in
BMC Bioinformatics, February 2021
DOI 10.1186/s12859-020-03932-5
Pubmed ID
Authors

Liangqun Lu, Kevin A. Townsend, Bernie J. Daigle

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 25%
Student > Bachelor 3 9%
Lecturer 2 6%
Researcher 2 6%
Student > Ph. D. Student 2 6%
Other 5 16%
Unknown 10 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 22%
Agricultural and Biological Sciences 4 13%
Computer Science 3 9%
Medicine and Dentistry 3 9%
Immunology and Microbiology 1 3%
Other 3 9%
Unknown 11 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 March 2021.
All research outputs
#13,409,247
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#4,062
of 7,388 outputs
Outputs of similar age
#232,643
of 506,364 outputs
Outputs of similar age from BMC Bioinformatics
#87
of 138 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 44th percentile – i.e., 44% 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 506,364 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 53% of its contemporaries.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.