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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RNA-seq assistant: machine learning based methods to identify more transcriptional regulated genes
|
|---|---|
| Published in |
BMC Genomics, July 2018
|
| DOI | 10.1186/s12864-018-4932-2 |
| Pubmed ID | |
| Authors |
Likai Wang, Yanpeng Xi, Sibum Sung, Hong Qiao |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 22% |
| United States | 1 | 11% |
| United Kingdom | 1 | 11% |
| France | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 56% |
| Members of the public | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 165 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 22% |
| Researcher | 24 | 15% |
| Student > Master | 20 | 12% |
| Student > Bachelor | 13 | 8% |
| Student > Doctoral Student | 11 | 7% |
| Other | 21 | 13% |
| Unknown | 40 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 36 | 22% |
| Agricultural and Biological Sciences | 31 | 19% |
| Computer Science | 11 | 7% |
| Engineering | 8 | 5% |
| Medicine and Dentistry | 8 | 5% |
| Other | 21 | 13% |
| Unknown | 50 | 30% |
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 08 August 2019.
All research outputs
#3,047,818
of 26,017,215 outputs
Outputs from BMC Genomics
#924
of 11,400 outputs
Outputs of similar age
#57,039
of 343,941 outputs
Outputs of similar age from BMC Genomics
#24
of 187 outputs
Altmetric has tracked 26,017,215 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 11,400 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 91% 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 343,941 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 83% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.