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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads
|
|---|---|
| Published in |
BMC Bioinformatics, October 2020
|
| DOI | 10.1186/s12859-020-03779-w |
| Pubmed ID | |
| Authors |
Xingyu Liao, Xin Gao, Xiankai Zhang, Fang-Xiang Wu, Jianxin Wang |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 29% |
| India | 1 | 14% |
| Sweden | 1 | 14% |
| Netherlands | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 24% |
| Student > Doctoral Student | 2 | 12% |
| Student > Master | 2 | 12% |
| Professor | 1 | 6% |
| Librarian | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 6 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 24% |
| Environmental Science | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Agricultural and Biological Sciences | 1 | 6% |
| Computer Science | 1 | 6% |
| Other | 3 | 18% |
| Unknown | 6 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 November 2020.
All research outputs
#3,325,874
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,186
of 7,400 outputs
Outputs of similar age
#85,953
of 420,645 outputs
Outputs of similar age from BMC Bioinformatics
#30
of 176 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 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 83% 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 420,645 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 176 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.