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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A dropout-regularized classifier development approach optimized for precision medicine test discovery from omics data
|
|---|---|
| Published in |
BMC Bioinformatics, June 2019
|
| DOI | 10.1186/s12859-019-2922-2 |
| Pubmed ID | |
| Authors |
Joanna Roder, Carlos Oliveira, Lelia Net, Maxim Tsypin, Benjamin Linstid, Heinrich Roder |
X Demographics
The data shown below were collected from the profiles of 4 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 | 25% |
| Korea, Republic of | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 25% |
| Other | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Ph. D. Student | 3 | 8% |
| Lecturer > Senior Lecturer | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 15 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 13% |
| Medicine and Dentistry | 4 | 10% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Nursing and Health Professions | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 8 | 20% |
| Unknown | 17 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 June 2019.
All research outputs
#15,047,580
of 23,150,406 outputs
Outputs from BMC Bioinformatics
#5,094
of 7,339 outputs
Outputs of similar age
#206,401
of 353,827 outputs
Outputs of similar age from BMC Bioinformatics
#119
of 186 outputs
Altmetric has tracked 23,150,406 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 353,827 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.