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Mendeley readers
Attention Score in Context
Title |
A resource for benchmarking the usefulness of protein structure models
|
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Published in |
BMC Bioinformatics, August 2012
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DOI | 10.1186/1471-2105-13-188 |
Pubmed ID | |
Authors |
Daniel Carbajo, Anna Tramontano |
Abstract |
Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. |
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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 2 | 8% |
Spain | 1 | 4% |
Canada | 1 | 4% |
Unknown | 22 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 27% |
Student > Ph. D. Student | 7 | 27% |
Student > Master | 5 | 19% |
Lecturer | 1 | 4% |
Student > Bachelor | 1 | 4% |
Other | 4 | 15% |
Unknown | 1 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 11 | 42% |
Computer Science | 5 | 19% |
Biochemistry, Genetics and Molecular Biology | 4 | 15% |
Mathematics | 1 | 4% |
Immunology and Microbiology | 1 | 4% |
Other | 2 | 8% |
Unknown | 2 | 8% |
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 06 August 2012.
All research outputs
#15,248,503
of 22,673,450 outputs
Outputs from BMC Bioinformatics
#5,361
of 7,247 outputs
Outputs of similar age
#104,584
of 164,813 outputs
Outputs of similar age from BMC Bioinformatics
#67
of 107 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 164,813 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.