The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing
|
|---|---|
| Published in |
Frontiers in Genetics, November 2020
|
| DOI | 10.3389/fgene.2020.505441 |
| Pubmed ID | |
| Authors |
Xiao Dong, Lei Zhang, Xiaoxiao Hao, Tao Wang, Jan Vijg |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 2 | 18% |
| Australia | 1 | 9% |
| Ecuador | 1 | 9% |
| Switzerland | 1 | 9% |
| Italy | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 64% |
| Scientists | 2 | 18% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 30% |
| Researcher | 5 | 17% |
| Student > Postgraduate | 3 | 10% |
| Student > Master | 3 | 10% |
| Student > Doctoral Student | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 47% |
| Agricultural and Biological Sciences | 4 | 13% |
| Medicine and Dentistry | 2 | 7% |
| Computer Science | 1 | 3% |
| Materials Science | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 8 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 03 March 2021.
All research outputs
#2,698,830
of 23,577,761 outputs
Outputs from Frontiers in Genetics
#691
of 12,603 outputs
Outputs of similar age
#61,811
of 379,933 outputs
Outputs of similar age from Frontiers in Genetics
#34
of 444 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,603 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 94% 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 379,933 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 83% of its contemporaries.
We're also able to compare this research output to 444 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 92% of its contemporaries.