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Mendeley readers
Attention Score in Context
| 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 231 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 | 210 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 64 | 28% |
| Researcher | 49 | 21% |
| Student > Master | 27 | 12% |
| Professor > Associate Professor | 12 | 5% |
| Student > Bachelor | 12 | 5% |
| Other | 39 | 17% |
| Unknown | 28 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 62 | 27% |
| Agricultural and Biological Sciences | 60 | 26% |
| Engineering | 17 | 7% |
| Medicine and Dentistry | 16 | 7% |
| Biochemistry, Genetics and Molecular Biology | 10 | 4% |
| Other | 30 | 13% |
| Unknown | 36 | 16% |
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
#4,778,877
of 23,106,390 outputs
Outputs from BMC Bioinformatics
#1,825
of 7,330 outputs
Outputs of similar age
#12,296
of 66,832 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 53 outputs
Altmetric has tracked 23,106,390 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 7,330 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 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 66,832 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 53 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.