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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of Cell Penetrating Peptides by Support Vector Machines
|
|---|---|
| Published in |
PLoS Computational Biology, July 2011
|
| DOI | 10.1371/journal.pcbi.1002101 |
| Pubmed ID | |
| Authors |
William S. Sanders, C. Ian Johnston, Susan M. Bridges, Shane C. Burgess, Kenneth O. Willeford |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 1% |
| United States | 2 | 1% |
| Brazil | 1 | <1% |
| India | 1 | <1% |
| Italy | 1 | <1% |
| Argentina | 1 | <1% |
| Mexico | 1 | <1% |
| Japan | 1 | <1% |
| China | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 148 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 23% |
| Researcher | 32 | 20% |
| Student > Master | 18 | 11% |
| Student > Bachelor | 12 | 8% |
| Professor > Associate Professor | 9 | 6% |
| Other | 26 | 16% |
| Unknown | 26 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 30% |
| Chemistry | 21 | 13% |
| Biochemistry, Genetics and Molecular Biology | 20 | 13% |
| Computer Science | 18 | 11% |
| Engineering | 5 | 3% |
| Other | 17 | 11% |
| Unknown | 30 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 20 February 2024.
All research outputs
#3,799,086
of 25,374,917 outputs
Outputs from PLoS Computational Biology
#3,291
of 8,960 outputs
Outputs of similar age
#18,732
of 128,483 outputs
Outputs of similar age from PLoS Computational Biology
#19
of 67 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 63% 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 128,483 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 67 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 71% of its contemporaries.