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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Benchmarking of computational error-correction methods for next-generation sequencing data
|
|---|---|
| Published in |
Genome Biology, March 2020
|
| DOI | 10.1186/s13059-020-01988-3 |
| Pubmed ID | |
| Authors |
Keith Mitchell, Jaqueline J. Brito, Igor Mandric, Qiaozhen Wu, Sergey Knyazev, Sei Chang, Lana S. Martin, Aaron Karlsberg, Ekaterina Gerasimov, Russell Littman, Brian L. Hill, Nicholas C. Wu, Harry Taegyun Yang, Kevin Hsieh, Linus Chen, Eli Littman, Taylor Shabani, German Enik, Douglas Yao, Ren Sun, Jan Schroeder, Eleazar Eskin, Alex Zelikovsky, Pavel Skums, Mihai Pop, Serghei Mangul |
X Demographics
The data shown below were collected from the profiles of 73 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 | 17 | 23% |
| United Kingdom | 8 | 11% |
| Germany | 4 | 5% |
| Spain | 3 | 4% |
| Venezuela, Bolivarian Republic of | 2 | 3% |
| Canada | 2 | 3% |
| Italy | 1 | 1% |
| Thailand | 1 | 1% |
| Netherlands | 1 | 1% |
| Other | 10 | 14% |
| Unknown | 24 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 42 | 58% |
| Members of the public | 29 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 1% |
| Practitioners (doctors, other healthcare professionals) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 103 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 20% |
| Student > Master | 16 | 16% |
| Researcher | 15 | 15% |
| Student > Bachelor | 9 | 9% |
| Student > Doctoral Student | 3 | 3% |
| Other | 10 | 10% |
| Unknown | 29 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 18% |
| Agricultural and Biological Sciences | 18 | 17% |
| Medicine and Dentistry | 7 | 7% |
| Computer Science | 6 | 6% |
| Immunology and Microbiology | 5 | 5% |
| Other | 11 | 11% |
| Unknown | 37 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 39. 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 13 September 2020.
All research outputs
#1,047,129
of 25,387,668 outputs
Outputs from Genome Biology
#754
of 4,470 outputs
Outputs of similar age
#28,172
of 404,770 outputs
Outputs of similar age from Genome Biology
#19
of 80 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 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 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 404,770 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 93% of its contemporaries.
We're also able to compare this research output to 80 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.