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X Demographics
Mendeley readers
Attention Score in Context
| Title |
High performance transcription factor-DNA docking with GPU computing
|
|---|---|
| Published in |
Proteome Science, June 2012
|
| DOI | 10.1186/1477-5956-10-s1-s17 |
| Pubmed ID | |
| Authors |
Jiadong Wu, Bo Hong, Takako Takeda, Jun-tao Guo |
| Abstract |
Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. |
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 % |
|---|---|---|
| Japan | 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 6% |
| Unknown | 15 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 31% |
| Student > Ph. D. Student | 5 | 31% |
| Student > Master | 3 | 19% |
| Professor | 1 | 6% |
| Student > Postgraduate | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 44% |
| Biochemistry, Genetics and Molecular Biology | 3 | 19% |
| Computer Science | 2 | 13% |
| Mathematics | 1 | 6% |
| Psychology | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 1 | 6% |
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 11 April 2013.
All research outputs
#18,335,133
of 22,705,019 outputs
Outputs from Proteome Science
#132
of 189 outputs
Outputs of similar age
#126,129
of 164,055 outputs
Outputs of similar age from Proteome Science
#3
of 3 outputs
Altmetric has tracked 22,705,019 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 189 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 16th percentile – i.e., 16% 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 164,055 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.