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Mendeley readers
Attention Score in Context
Title |
gEMpicker: a highly parallel GPU-accelerated particle picking tool for cryo-electron microscopy
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Published in |
BMC Molecular and Cell Biology, October 2013
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DOI | 10.1186/1472-6807-13-25 |
Pubmed ID | |
Authors |
Thai V Hoang, Xavier Cavin, Patrick Schultz, David W Ritchie |
Abstract |
Picking images of particles in cryo-electron micrographs is an important step in solving the 3D structures of large macromolecular assemblies. However, in order to achieve sub-nanometre resolution it is often necessary to capture and process many thousands or even several millions of 2D particle images. Thus, a computational bottleneck in reaching high resolution is the accurate and automatic picking of particles from raw cryo-electron micrographs. |
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 % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 1 | 3% |
Russia | 1 | 3% |
Unknown | 34 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 25% |
Student > Ph. D. Student | 9 | 25% |
Student > Master | 4 | 11% |
Student > Doctoral Student | 3 | 8% |
Other | 2 | 6% |
Other | 5 | 14% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 10 | 28% |
Agricultural and Biological Sciences | 8 | 22% |
Computer Science | 8 | 22% |
Chemistry | 2 | 6% |
Medicine and Dentistry | 2 | 6% |
Other | 1 | 3% |
Unknown | 5 | 14% |
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 22 October 2013.
All research outputs
#22,758,309
of 25,371,288 outputs
Outputs from BMC Molecular and Cell Biology
#1,054
of 1,233 outputs
Outputs of similar age
#198,585
of 224,352 outputs
Outputs of similar age from BMC Molecular and Cell Biology
#27
of 28 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,233 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% 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 224,352 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.