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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles
|
|---|---|
| Published in |
BMC Bioinformatics, February 2020
|
| DOI | 10.1186/s12859-020-3388-y |
| Pubmed ID | |
| Authors |
Xudong Zhao, Qing Jiao, Hangyu Li, Yiming Wu, Hanxu Wang, Shan Huang, Guohua Wang |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 22% |
| Student > Ph. D. Student | 5 | 19% |
| Student > Bachelor | 4 | 15% |
| Student > Master | 3 | 11% |
| Student > Doctoral Student | 2 | 7% |
| Other | 3 | 11% |
| Unknown | 4 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 33% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Agricultural and Biological Sciences | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Sports and Recreations | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 8 | 30% |
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 16 February 2020.
All research outputs
#3,893,654
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,447
of 7,400 outputs
Outputs of similar age
#89,187
of 452,170 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 164 outputs
Altmetric has tracked 23,577,654 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 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 80% 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 452,170 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 80% of its contemporaries.
We're also able to compare this research output to 164 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.