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Attention Score in Context
Title |
Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature
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Published in |
BMC Bioinformatics, August 2011
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DOI | 10.1186/1471-2105-12-341 |
Pubmed ID | |
Authors |
Wen Zhang, Yi Xiong, Meng Zhao, Hua Zou, Xinghuo Ye, Juan Liu |
Abstract |
Antigen-antibody interactions are key events in immune system, which provide important clues to the immune processes and responses. In Antigen-antibody interactions, the specific sites on the antigens that are directly bound by the B-cell produced antibodies are well known as B-cell epitopes. The identification of epitopes is a hot topic in bioinformatics because of their potential use in the epitope-based drug design. Although most B-cell epitopes are discontinuous (or conformational), insufficient effort has been put into the conformational epitope prediction, and the performance of existing methods is far from satisfaction. |
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 Kingdom | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 2% |
Brazil | 2 | 2% |
India | 1 | 1% |
United States | 1 | 1% |
Unknown | 77 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 30% |
Researcher | 11 | 13% |
Student > Master | 9 | 11% |
Student > Bachelor | 8 | 10% |
Student > Doctoral Student | 6 | 7% |
Other | 16 | 19% |
Unknown | 8 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 25 | 30% |
Computer Science | 18 | 22% |
Biochemistry, Genetics and Molecular Biology | 14 | 17% |
Immunology and Microbiology | 8 | 10% |
Medicine and Dentistry | 3 | 4% |
Other | 4 | 5% |
Unknown | 11 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 31 August 2022.
All research outputs
#4,617,308
of 23,206,358 outputs
Outputs from BMC Bioinformatics
#1,727
of 7,354 outputs
Outputs of similar age
#24,595
of 124,303 outputs
Outputs of similar age from BMC Bioinformatics
#25
of 71 outputs
Altmetric has tracked 23,206,358 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,354 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 76% of its peers.
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 124,303 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.