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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Support Vector Machines and Kernels for Computational Biology
|
|---|---|
| Published in |
PLoS Computational Biology, October 2008
|
| DOI | 10.1371/journal.pcbi.1000173 |
| Pubmed ID | |
| Authors |
Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,035 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 47 | 5% |
| Germany | 19 | 2% |
| United Kingdom | 17 | 2% |
| France | 6 | <1% |
| Spain | 6 | <1% |
| Brazil | 6 | <1% |
| Switzerland | 4 | <1% |
| Canada | 4 | <1% |
| Australia | 4 | <1% |
| Other | 45 | 4% |
| Unknown | 877 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 256 | 25% |
| Researcher | 230 | 22% |
| Student > Master | 139 | 13% |
| Professor > Associate Professor | 60 | 6% |
| Student > Bachelor | 58 | 6% |
| Other | 171 | 17% |
| Unknown | 121 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 285 | 28% |
| Computer Science | 223 | 22% |
| Biochemistry, Genetics and Molecular Biology | 106 | 10% |
| Engineering | 86 | 8% |
| Mathematics | 33 | 3% |
| Other | 158 | 15% |
| Unknown | 144 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 19 November 2017.
All research outputs
#17,932,284
of 26,017,215 outputs
Outputs from PLoS Computational Biology
#7,547
of 9,035 outputs
Outputs of similar age
#93,517
of 109,026 outputs
Outputs of similar age from PLoS Computational Biology
#39
of 48 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,035 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 109,026 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.