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Mendeley readers
Attention Score in Context
| Title |
CPORT: A Consensus Interface Predictor and Its Performance in Prediction-Driven Docking with HADDOCK
|
|---|---|
| Published in |
PLOS ONE, March 2011
|
| DOI | 10.1371/journal.pone.0017695 |
| Pubmed ID | |
| Authors |
Sjoerd J. de Vries, Alexandre M. J. J. Bonvin |
| Abstract |
Macromolecular complexes are the molecular machines of the cell. Knowledge at the atomic level is essential to understand and influence their function. However, their number is huge and a significant fraction is extremely difficult to study using classical structural methods such as NMR and X-ray crystallography. Therefore, the importance of large-scale computational approaches in structural biology is evident. This study combines two of these computational approaches, interface prediction and docking, to obtain atomic-level structures of protein-protein complexes, starting from their unbound components. |
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 292 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Ireland | 1 | <1% |
| Italy | 1 | <1% |
| Australia | 1 | <1% |
| United Kingdom | 1 | <1% |
| Japan | 1 | <1% |
| United States | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 283 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 18% |
| Student > Bachelor | 51 | 17% |
| Researcher | 39 | 13% |
| Student > Master | 36 | 12% |
| Student > Doctoral Student | 14 | 5% |
| Other | 39 | 13% |
| Unknown | 60 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 97 | 33% |
| Agricultural and Biological Sciences | 66 | 23% |
| Chemistry | 14 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 3% |
| Computer Science | 7 | 2% |
| Other | 30 | 10% |
| Unknown | 70 | 24% |
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 15 November 2013.
All research outputs
#18,353,475
of 22,729,647 outputs
Outputs from PLOS ONE
#154,213
of 194,027 outputs
Outputs of similar age
#95,226
of 108,514 outputs
Outputs of similar age from PLOS ONE
#1,230
of 1,438 outputs
Altmetric has tracked 22,729,647 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,027 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 10th percentile – i.e., 10% 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 108,514 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,438 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.