You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Batch correction evaluation framework using a-priori gene-gene associations: applied to the GTEx dataset
|
|---|---|
| Published in |
BMC Bioinformatics, May 2019
|
| DOI | 10.1186/s12859-019-2855-9 |
| Pubmed ID | |
| Authors |
Judith Somekh, Shai S Shen-Orr, Isaac S Kohane |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| Finland | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 43 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 21% |
| Student > Ph. D. Student | 5 | 12% |
| Researcher | 4 | 9% |
| Professor | 3 | 7% |
| Other | 3 | 7% |
| Other | 11 | 26% |
| Unknown | 8 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 21% |
| Biochemistry, Genetics and Molecular Biology | 8 | 19% |
| Agricultural and Biological Sciences | 6 | 14% |
| Engineering | 4 | 9% |
| Nursing and Health Professions | 2 | 5% |
| Other | 4 | 9% |
| Unknown | 10 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 30 May 2019.
All research outputs
#12,935,734
of 23,149,216 outputs
Outputs from BMC Bioinformatics
#3,662
of 7,339 outputs
Outputs of similar age
#158,223
of 350,248 outputs
Outputs of similar age from BMC Bioinformatics
#100
of 205 outputs
Altmetric has tracked 23,149,216 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% 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 48th percentile – i.e., 48% 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 350,248 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 54% of its contemporaries.
We're also able to compare this research output to 205 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.