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An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets

Overview of attention for article published in BMC Bioinformatics, August 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

twitter
11 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
63 Mendeley
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Title
An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets
Published in
BMC Bioinformatics, August 2019
DOI 10.1186/s12859-019-2994-z
Pubmed ID
Authors

Arezo Torang, Paraag Gupta, David J. Klinke

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 17%
Researcher 11 17%
Student > Master 9 14%
Student > Ph. D. Student 8 13%
Student > Postgraduate 5 8%
Other 8 13%
Unknown 11 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 32%
Agricultural and Biological Sciences 10 16%
Computer Science 6 10%
Medicine and Dentistry 4 6%
Immunology and Microbiology 4 6%
Other 7 11%
Unknown 12 19%

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 17 October 2019.
All research outputs
#4,192,577
of 16,033,582 outputs
Outputs from BMC Bioinformatics
#1,738
of 5,809 outputs
Outputs of similar age
#85,491
of 264,031 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 16,033,582 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 5,809 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 264,031 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 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them