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 |
Machine Learning SNP Based Prediction for Precision Medicine
|
|---|---|
| Published in |
Frontiers in Genetics, March 2019
|
| DOI | 10.3389/fgene.2019.00267 |
| Pubmed ID | |
| Authors |
Daniel Sik Wai Ho, William Schierding, Melissa Wake, Richard Saffery, Justin O’Sullivan |
X Demographics
The data shown below were collected from the profiles of 11 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 | 27% |
| Guinea | 1 | 9% |
| United Kingdom | 1 | 9% |
| Switzerland | 1 | 9% |
| New Zealand | 1 | 9% |
| Unknown | 4 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 64% |
| Scientists | 4 | 36% |
Mendeley readers
The data shown below were compiled from readership statistics for 466 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 466 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 82 | 18% |
| Student > Master | 62 | 13% |
| Researcher | 60 | 13% |
| Student > Bachelor | 33 | 7% |
| Student > Postgraduate | 21 | 5% |
| Other | 69 | 15% |
| Unknown | 139 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 109 | 23% |
| Computer Science | 57 | 12% |
| Agricultural and Biological Sciences | 38 | 8% |
| Medicine and Dentistry | 38 | 8% |
| Neuroscience | 15 | 3% |
| Other | 59 | 13% |
| Unknown | 150 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 29 September 2021.
All research outputs
#2,138,119
of 23,136,540 outputs
Outputs from Frontiers in Genetics
#501
of 12,179 outputs
Outputs of similar age
#50,327
of 351,782 outputs
Outputs of similar age from Frontiers in Genetics
#27
of 359 outputs
Altmetric has tracked 23,136,540 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,179 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 95% 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 351,782 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 85% of its contemporaries.
We're also able to compare this research output to 359 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.