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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data
|
|---|---|
| Published in |
BMC Bioinformatics, June 2019
|
| DOI | 10.1186/s12859-019-2769-6 |
| Pubmed ID | |
| Authors |
Jiajie Peng, Xiaoyu Wang, Xuequn Shang |
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 % |
|---|---|---|
| France | 2 | 22% |
| Australia | 1 | 11% |
| United States | 1 | 11% |
| United Kingdom | 1 | 11% |
| Austria | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 116 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 22% |
| Researcher | 15 | 13% |
| Student > Master | 12 | 10% |
| Student > Bachelor | 11 | 9% |
| Student > Doctoral Student | 3 | 3% |
| Other | 6 | 5% |
| Unknown | 44 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 22% |
| Computer Science | 17 | 15% |
| Agricultural and Biological Sciences | 10 | 9% |
| Neuroscience | 4 | 3% |
| Engineering | 3 | 3% |
| Other | 12 | 10% |
| Unknown | 45 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 07 March 2024.
All research outputs
#4,108,801
of 25,405,598 outputs
Outputs from BMC Bioinformatics
#1,351
of 7,701 outputs
Outputs of similar age
#77,972
of 368,291 outputs
Outputs of similar age from BMC Bioinformatics
#47
of 190 outputs
Altmetric has tracked 25,405,598 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,701 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 82% 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 368,291 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 78% of its contemporaries.
We're also able to compare this research output to 190 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.