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Seagull: lasso, group lasso and sparse-group lasso regularization for linear regression models via proximal gradient descent

Overview of attention for article published in BMC Bioinformatics, September 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
10 X users

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Seagull: lasso, group lasso and sparse-group lasso regularization for linear regression models via proximal gradient descent
Published in
BMC Bioinformatics, September 2020
DOI 10.1186/s12859-020-03725-w
Pubmed ID
Authors

Jan Klosa, Noah Simon, Pål Olof Westermark, Volkmar Liebscher, Dörte Wittenburg

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

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 27%
Researcher 7 23%
Student > Bachelor 2 7%
Other 1 3%
Lecturer 1 3%
Other 3 10%
Unknown 8 27%
Readers by discipline Count As %
Mathematics 4 13%
Agricultural and Biological Sciences 3 10%
Engineering 2 7%
Biochemistry, Genetics and Molecular Biology 2 7%
Computer Science 2 7%
Other 6 20%
Unknown 11 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 03 October 2020.
All research outputs
#6,982,354
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#2,645
of 7,387 outputs
Outputs of similar age
#148,611
of 403,543 outputs
Outputs of similar age from BMC Bioinformatics
#63
of 152 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 63% 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 403,543 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 62% of its contemporaries.
We're also able to compare this research output to 152 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 59% of its contemporaries.