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Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems

Overview of attention for article published in BMC Bioinformatics, June 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
3 X users
patent
1 patent
googleplus
1 Google+ user
f1000
1 research highlight platform

Readers on

mendeley
729 Mendeley
citeulike
7 CiteULike
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Title
Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems
Published in
BMC Bioinformatics, June 2011
DOI 10.1186/1471-2105-12-253
Pubmed ID
Authors

Kim-Anh Lê Cao, Simon Boitard, Philippe Besse

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 729 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 1%
United Kingdom 3 <1%
Germany 2 <1%
France 2 <1%
Italy 2 <1%
Poland 2 <1%
Netherlands 1 <1%
Australia 1 <1%
Chile 1 <1%
Other 8 1%
Unknown 699 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 180 25%
Student > Ph. D. Student 161 22%
Student > Master 70 10%
Student > Bachelor 53 7%
Student > Doctoral Student 39 5%
Other 107 15%
Unknown 119 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 215 29%
Biochemistry, Genetics and Molecular Biology 111 15%
Chemistry 42 6%
Computer Science 35 5%
Medicine and Dentistry 34 5%
Other 146 20%
Unknown 146 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 12 December 2023.
All research outputs
#4,978,221
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,764
of 7,793 outputs
Outputs of similar age
#25,172
of 131,406 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 107 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 76% 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 131,406 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 78% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.