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Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data

Overview of attention for article published in Machine Learning, July 2003
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

twitter
1 X user
patent
7 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
1653 Dimensions

Readers on

mendeley
1057 Mendeley
citeulike
10 CiteULike
Title
Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data
Published in
Machine Learning, July 2003
DOI 10.1023/a:1023949509487
Authors

Stefano Monti, Pablo Tamayo, Jill Mesirov, Todd Golub

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 1,057 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 20 2%
Germany 6 <1%
United Kingdom 5 <1%
Spain 4 <1%
Brazil 3 <1%
Canada 3 <1%
Israel 2 <1%
Italy 2 <1%
Latvia 1 <1%
Other 18 2%
Unknown 993 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 276 26%
Researcher 217 21%
Student > Master 115 11%
Student > Bachelor 53 5%
Student > Doctoral Student 50 5%
Other 175 17%
Unknown 171 16%
Readers by discipline Count As %
Computer Science 219 21%
Agricultural and Biological Sciences 207 20%
Biochemistry, Genetics and Molecular Biology 121 11%
Medicine and Dentistry 87 8%
Engineering 64 6%
Other 152 14%
Unknown 207 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 October 2022.
All research outputs
#3,484,692
of 25,837,817 outputs
Outputs from Machine Learning
#90
of 1,259 outputs
Outputs of similar age
#5,135
of 53,083 outputs
Outputs of similar age from Machine Learning
#1
of 3 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,259 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 92% 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 53,083 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 3 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