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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods
|
|---|---|
| Published in |
BMC Bioinformatics, October 2009
|
| DOI | 10.1186/1471-2105-10-365 |
| Pubmed ID | |
| Authors |
Stefano Lise, Cedric Archambeau, Massimiliano Pontil, David T Jones |
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 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 3% |
| Germany | 2 | 2% |
| Switzerland | 2 | 2% |
| Korea, Republic of | 1 | <1% |
| Portugal | 1 | <1% |
| Australia | 1 | <1% |
| China | 1 | <1% |
| Spain | 1 | <1% |
| Serbia | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 115 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 28% |
| Researcher | 35 | 27% |
| Student > Master | 16 | 12% |
| Student > Doctoral Student | 8 | 6% |
| Professor > Associate Professor | 6 | 5% |
| Other | 13 | 10% |
| Unknown | 15 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 47 | 36% |
| Biochemistry, Genetics and Molecular Biology | 20 | 16% |
| Chemistry | 14 | 11% |
| Computer Science | 14 | 11% |
| Engineering | 6 | 5% |
| Other | 10 | 8% |
| Unknown | 18 | 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 30 November 2023.
All research outputs
#22,312,396
of 24,903,209 outputs
Outputs from BMC Bioinformatics
#7,184
of 7,606 outputs
Outputs of similar age
#99,054
of 103,125 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 63 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,606 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 1st percentile – i.e., 1% 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 103,125 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.