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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic variants and their interactions in disease risk prediction – machine learning and network perspectives
|
|---|---|
| Published in |
BioData Mining, March 2013
|
| DOI | 10.1186/1756-0381-6-5 |
| Pubmed ID | |
| Authors |
Sebastian Okser, Tapio Pahikkala, Tero Aittokallio |
X Demographics
The data shown below were collected from the profiles of 6 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 | 3 | 50% |
| United Kingdom | 1 | 17% |
| Côte d'Ivoire | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Germany | 3 | 2% |
| Israel | 2 | 1% |
| Switzerland | 1 | <1% |
| France | 1 | <1% |
| Hungary | 1 | <1% |
| Australia | 1 | <1% |
| Denmark | 1 | <1% |
| Argentina | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 162 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 56 | 32% |
| Researcher | 32 | 18% |
| Student > Master | 30 | 17% |
| Student > Bachelor | 8 | 5% |
| Other | 7 | 4% |
| Other | 25 | 14% |
| Unknown | 18 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 50 | 28% |
| Biochemistry, Genetics and Molecular Biology | 31 | 18% |
| Computer Science | 28 | 16% |
| Medicine and Dentistry | 14 | 8% |
| Mathematics | 8 | 5% |
| Other | 22 | 13% |
| Unknown | 23 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 July 2013.
All research outputs
#7,119,353
of 22,712,476 outputs
Outputs from BioData Mining
#153
of 307 outputs
Outputs of similar age
#61,232
of 194,019 outputs
Outputs of similar age from BioData Mining
#3
of 6 outputs
Altmetric has tracked 22,712,476 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 50% 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 194,019 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 68% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.