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Mendeley readers
Attention Score in Context
| Title |
Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers
|
|---|---|
| Published in |
BioData Mining, November 2011
|
| DOI | 10.1186/1756-0381-4-26 |
| Pubmed ID | |
| Authors |
J Nikolaj Dybowski, Mona Riemenschneider, Sascha Hauke, Martin Pyka, Jens Verheyen, Daniel Hoffmann, Dominik Heider |
| Abstract |
Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat. Highly specific and accurate tools to predict resistance to maturation inhibitors can help to identify patients, who might benefit from the usage of these new drugs. |
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 % |
|---|---|---|
| Poland | 1 | 4% |
| Germany | 1 | 4% |
| Unknown | 24 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 23% |
| Student > Master | 4 | 15% |
| Student > Ph. D. Student | 4 | 15% |
| Student > Postgraduate | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Other | 4 | 15% |
| Unknown | 3 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Agricultural and Biological Sciences | 5 | 19% |
| Computer Science | 4 | 15% |
| Psychology | 2 | 8% |
| Engineering | 2 | 8% |
| Other | 4 | 15% |
| Unknown | 4 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 11 June 2012.
All research outputs
#7,454,066
of 22,788,370 outputs
Outputs from BioData Mining
#161
of 307 outputs
Outputs of similar age
#47,224
of 141,697 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 22,788,370 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 45th percentile – i.e., 45% 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 141,697 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them