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X Demographics
Mendeley readers
Attention Score in Context
| Title |
lncDIFF: a novel quasi-likelihood method for differential expression analysis of non-coding RNA
|
|---|---|
| Published in |
BMC Genomics, July 2019
|
| DOI | 10.1186/s12864-019-5926-4 |
| Pubmed ID | |
| Authors |
Qian Li, Xiaoqing Yu, Ritu Chaudhary, Robbert J. C. Slebos, Christine H. Chung, Xuefeng Wang |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 36% |
| Student > Master | 3 | 12% |
| Student > Bachelor | 2 | 8% |
| Student > Doctoral Student | 2 | 8% |
| Researcher | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 6 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 32% |
| Agricultural and Biological Sciences | 3 | 12% |
| Computer Science | 2 | 8% |
| Mathematics | 1 | 4% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 8 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 04 July 2023.
All research outputs
#4,915,517
of 24,063,285 outputs
Outputs from BMC Genomics
#1,955
of 10,892 outputs
Outputs of similar age
#93,229
of 351,419 outputs
Outputs of similar age from BMC Genomics
#42
of 230 outputs
Altmetric has tracked 24,063,285 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,892 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 81% 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 351,419 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 230 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.