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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
|
|---|---|
| Published in |
Genome Biology, January 2020
|
| DOI | 10.1186/s13059-019-1850-9 |
| Pubmed ID | |
| Authors |
Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen |
X Demographics
The data shown below were collected from the profiles of 223 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 | 74 | 33% |
| Australia | 13 | 6% |
| Canada | 10 | 4% |
| United Kingdom | 9 | 4% |
| Germany | 9 | 4% |
| Japan | 4 | 2% |
| France | 4 | 2% |
| Italy | 3 | 1% |
| China | 3 | 1% |
| Other | 16 | 7% |
| Unknown | 78 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 130 | 58% |
| Members of the public | 88 | 39% |
| Practitioners (doctors, other healthcare professionals) | 4 | 2% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 865 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 865 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 163 | 19% |
| Researcher | 138 | 16% |
| Student > Master | 70 | 8% |
| Student > Bachelor | 68 | 8% |
| Student > Doctoral Student | 38 | 4% |
| Other | 93 | 11% |
| Unknown | 295 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 239 | 28% |
| Agricultural and Biological Sciences | 83 | 10% |
| Computer Science | 52 | 6% |
| Immunology and Microbiology | 38 | 4% |
| Medicine and Dentistry | 38 | 4% |
| Other | 102 | 12% |
| Unknown | 313 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 127. 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 20 February 2023.
All research outputs
#332,444
of 25,587,485 outputs
Outputs from Genome Biology
#146
of 4,492 outputs
Outputs of similar age
#8,409
of 479,418 outputs
Outputs of similar age from Genome Biology
#8
of 87 outputs
Altmetric has tracked 25,587,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% 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 has done particularly well, scoring higher than 96% 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 479,418 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 98% of its contemporaries.
We're also able to compare this research output to 87 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 91% of its contemporaries.