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Mendeley readers
Attention Score in Context
| Title |
Clustering cancer gene expression data: a comparative study
|
|---|---|
| Published in |
BMC Bioinformatics, November 2008
|
| DOI | 10.1186/1471-2105-9-497 |
| Pubmed ID | |
| Authors |
Marcilio CP de Souto, Ivan G Costa, Daniel SA de Araujo, Teresa B Ludermir, Alexander Schliep |
| Abstract |
The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using "classic" clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. |
Mendeley readers
The data shown below were compiled from readership statistics for 233 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| Russia | 2 | <1% |
| Brazil | 2 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| United Kingdom | 1 | <1% |
| Switzerland | 1 | <1% |
| Belgium | 1 | <1% |
| Malaysia | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 218 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 59 | 25% |
| Researcher | 46 | 20% |
| Student > Master | 37 | 16% |
| Student > Bachelor | 21 | 9% |
| Professor | 9 | 4% |
| Other | 33 | 14% |
| Unknown | 28 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 76 | 33% |
| Agricultural and Biological Sciences | 42 | 18% |
| Biochemistry, Genetics and Molecular Biology | 24 | 10% |
| Engineering | 13 | 6% |
| Medicine and Dentistry | 11 | 5% |
| Other | 31 | 13% |
| Unknown | 36 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 15 January 2019.
All research outputs
#7,453,827
of 22,787,797 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#47,552
of 165,162 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 45 outputs
Altmetric has tracked 22,787,797 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 165,162 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.