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Mendeley readers
Attention Score in Context
| Title |
A comprehensive system for evaluation of remote sequence similarity detection
|
|---|---|
| Published in |
BMC Bioinformatics, August 2007
|
| DOI | 10.1186/1471-2105-8-314 |
| Pubmed ID | |
| Authors |
Yuan Qi, Ruslan I Sadreyev, Yong Wang, Bong-Hyun Kim, Nick V Grishin |
| Abstract |
Accurate and sensitive performance evaluation is crucial for both effective development of better structure prediction methods based on sequence similarity, and for the comparative analysis of existing methods. Up to date, there has been no satisfactory comprehensive evaluation method that (i) is based on a large and statistically unbiased set of proteins with clearly defined relationships; and (ii) covers all performance aspects of sequence-based structure predictors, such as sensitivity and specificity, alignment accuracy and coverage, and structure template quality. |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 8% |
| United Kingdom | 1 | 4% |
| France | 1 | 4% |
| South Africa | 1 | 4% |
| Unknown | 20 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 24% |
| Researcher | 5 | 20% |
| Professor > Associate Professor | 3 | 12% |
| Student > Master | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 3 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 40% |
| Computer Science | 6 | 24% |
| Biochemistry, Genetics and Molecular Biology | 4 | 16% |
| Engineering | 2 | 8% |
| Medicine and Dentistry | 1 | 4% |
| Other | 0 | 0% |
| 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 19 March 2008.
All research outputs
#15,240,835
of 22,660,862 outputs
Outputs from BMC Bioinformatics
#5,353
of 7,241 outputs
Outputs of similar age
#58,856
of 68,641 outputs
Outputs of similar age from BMC Bioinformatics
#30
of 41 outputs
Altmetric has tracked 22,660,862 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 7,241 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 68,641 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.