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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Analysis of error profiles in deep next-generation sequencing data
|
|---|---|
| Published in |
Genome Biology, March 2019
|
| DOI | 10.1186/s13059-019-1659-6 |
| Pubmed ID | |
| Authors |
Xiaotu Ma, Ying Shao, Liqing Tian, Diane A. Flasch, Heather L. Mulder, Michael N. Edmonson, Yu Liu, Xiang Chen, Scott Newman, Joy Nakitandwe, Yongjin Li, Benshang Li, Shuhong Shen, Zhaoming Wang, Sheila Shurtleff, Leslie L. Robison, Shawn Levy, John Easton, Jinghui Zhang |
X Demographics
The data shown below were collected from the profiles of 54 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 | 14 | 26% |
| United Kingdom | 8 | 15% |
| Brazil | 2 | 4% |
| Australia | 2 | 4% |
| Kenya | 1 | 2% |
| Spain | 1 | 2% |
| France | 1 | 2% |
| Colombia | 1 | 2% |
| Korea, Democratic People's Republic of | 1 | 2% |
| Other | 6 | 11% |
| Unknown | 17 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 28 | 52% |
| Members of the public | 23 | 43% |
| Science communicators (journalists, bloggers, editors) | 2 | 4% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 379 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 379 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 70 | 18% |
| Researcher | 59 | 16% |
| Student > Master | 52 | 14% |
| Student > Bachelor | 25 | 7% |
| Student > Doctoral Student | 18 | 5% |
| Other | 47 | 12% |
| Unknown | 108 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 125 | 33% |
| Agricultural and Biological Sciences | 67 | 18% |
| Medicine and Dentistry | 20 | 5% |
| Computer Science | 10 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 1% |
| Other | 30 | 8% |
| Unknown | 122 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 63. 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 18 June 2023.
All research outputs
#690,816
of 25,827,956 outputs
Outputs from Genome Biology
#429
of 4,520 outputs
Outputs of similar age
#15,843
of 366,440 outputs
Outputs of similar age from Genome Biology
#14
of 59 outputs
Altmetric has tracked 25,827,956 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 4,520 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 90% 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 366,440 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 95% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.