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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies
|
|---|---|
| Published in |
Genome Biology, December 2022
|
| DOI | 10.1186/s13059-022-02816-6 |
| Pubmed ID | |
| Authors |
Keyur Talsania, Tsai-wei Shen, Xiongfong Chen, Erich Jaeger, Zhipan Li, Zhong Chen, Wanqiu Chen, Bao Tran, Rebecca Kusko, Limin Wang, Andy Wing Chun Pang, Zhaowei Yang, Sulbha Choudhari, Michael Colgan, Li Tai Fang, Andrew Carroll, Jyoti Shetty, Yuliya Kriga, Oksana German, Tatyana Smirnova, Tiantain Liu, Jing Li, Ben Kellman, Karl Hong, Alex R. Hastie, Aparna Natarajan, Ali Moshrefi, Anastasiya Granat, Tiffany Truong, Robin Bombardi, Veronnica Mankinen, Daoud Meerzaman, Christopher E. Mason, Jack Collins, Eric Stahlberg, Chunlin Xiao, Charles Wang, Wenming Xiao, Yongmei Zhao |
X Demographics
The data shown below were collected from the profiles of 20 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 States | 7 | 35% |
| United Kingdom | 2 | 10% |
| Switzerland | 1 | 5% |
| France | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 8 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 75% |
| Scientists | 4 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 29% |
| Student > Ph. D. Student | 3 | 11% |
| Student > Bachelor | 2 | 7% |
| Other | 2 | 7% |
| Student > Master | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 7 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 29% |
| Agricultural and Biological Sciences | 6 | 21% |
| Engineering | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Psychology | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 32% |
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 28 March 2024.
All research outputs
#3,037,762
of 25,582,611 outputs
Outputs from Genome Biology
#2,267
of 4,492 outputs
Outputs of similar age
#61,382
of 482,751 outputs
Outputs of similar age from Genome Biology
#40
of 61 outputs
Altmetric has tracked 25,582,611 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 4,492 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 49th percentile – i.e., 49% 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 482,751 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 87% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.