| 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
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,056 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 | 992 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 275 | 26% |
| Researcher | 216 | 20% |
| Student > Master | 115 | 11% |
| Student > Bachelor | 52 | 5% |
| Student > Doctoral Student | 50 | 5% |
| Other | 177 | 17% |
| Unknown | 171 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 218 | 21% |
| Agricultural and Biological Sciences | 206 | 20% |
| Biochemistry, Genetics and Molecular Biology | 121 | 11% |
| Medicine and Dentistry | 87 | 8% |
| Engineering | 64 | 6% |
| Other | 153 | 14% |
| Unknown | 207 | 20% |
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