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Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

Overview of attention for article published in BMC Bioinformatics, April 2006
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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 (71st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
227 Dimensions

Readers on

mendeley
219 Mendeley
citeulike
8 CiteULike
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Title
Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data
Published in
BMC Bioinformatics, April 2006
DOI 10.1186/1471-2105-7-197
Pubmed ID
Authors

Xuegong Zhang, Xin Lu, Qian Shi, Xiu-qin Xu, Hon-chiu E Leung, Lyndsay N Harris, James D Iglehart, Alexander Miron, Jun S Liu, Wing H Wong

Mendeley readers

The data shown below were compiled from readership statistics for 219 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Germany 3 1%
United Kingdom 3 1%
China 2 <1%
India 1 <1%
Egypt 1 <1%
France 1 <1%
Korea, Republic of 1 <1%
Belgium 1 <1%
Other 2 <1%
Unknown 198 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 29%
Researcher 46 21%
Student > Master 28 13%
Professor > Associate Professor 12 5%
Student > Bachelor 11 5%
Other 38 17%
Unknown 20 9%
Readers by discipline Count As %
Computer Science 61 28%
Agricultural and Biological Sciences 60 27%
Engineering 17 8%
Medicine and Dentistry 15 7%
Biochemistry, Genetics and Molecular Biology 9 4%
Other 29 13%
Unknown 28 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 06 January 2021.
All research outputs
#4,019,763
of 19,891,915 outputs
Outputs from BMC Bioinformatics
#1,663
of 6,677 outputs
Outputs of similar age
#80,972
of 289,998 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 35 outputs
Altmetric has tracked 19,891,915 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,677 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 73% 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 289,998 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 71% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.