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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MADOKA: an ultra-fast approach for large-scale protein structure similarity searching
|
|---|---|
| Published in |
BMC Bioinformatics, December 2019
|
| DOI | 10.1186/s12859-019-3235-1 |
| Pubmed ID | |
| Authors |
Lei Deng, Guolun Zhong, Chenzhe Liu, Judong Luo, Hui Liu |
X Demographics
The data shown below were collected from the profiles of 89 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 26 | 29% |
| United States | 5 | 6% |
| United Kingdom | 2 | 2% |
| Italy | 2 | 2% |
| Australia | 1 | 1% |
| Côte d'Ivoire | 1 | 1% |
| China | 1 | 1% |
| Unknown | 51 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 72 | 81% |
| Scientists | 16 | 18% |
| Unknown | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 24% |
| Student > Ph. D. Student | 8 | 19% |
| Student > Master | 5 | 12% |
| Student > Postgraduate | 3 | 7% |
| Lecturer > Senior Lecturer | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 12 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 31% |
| Agricultural and Biological Sciences | 6 | 14% |
| Engineering | 2 | 5% |
| Immunology and Microbiology | 1 | 2% |
| Environmental Science | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 17 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 62. 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 28 May 2021.
All research outputs
#705,312
of 25,768,270 outputs
Outputs from BMC Bioinformatics
#37
of 7,743 outputs
Outputs of similar age
#17,077
of 481,443 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 211 outputs
Altmetric has tracked 25,768,270 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,743 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 99% 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 481,443 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 211 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.