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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation of multiple protein docking structures using correctly predicted pairwise subunits
|
|---|---|
| Published in |
BMC Bioinformatics, March 2012
|
| DOI | 10.1186/1471-2105-13-s2-s6 |
| Pubmed ID | |
| Authors |
Juan Esquivel-Rodríguez, Daisuke Kihara |
| Abstract |
Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 6% |
| United States | 1 | 6% |
| Unknown | 15 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 29% |
| Professor | 3 | 18% |
| Student > Ph. D. Student | 3 | 18% |
| Professor > Associate Professor | 2 | 12% |
| Other | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 53% |
| Biochemistry, Genetics and Molecular Biology | 4 | 24% |
| Computer Science | 3 | 18% |
| Unknown | 1 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 May 2013.
All research outputs
#13,754,419
of 23,318,744 outputs
Outputs from BMC Bioinformatics
#4,298
of 7,384 outputs
Outputs of similar age
#89,169
of 157,929 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 62 outputs
Altmetric has tracked 23,318,744 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,384 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 38th percentile – i.e., 38% 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 157,929 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.