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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Variant interpretation through Bayesian fusion of frequency and genomic knowledge
|
|---|---|
| Published in |
Genome Medicine, January 2015
|
| DOI | 10.1186/s13073-015-0129-3 |
| Pubmed ID | |
| Authors |
Chad A Shaw, Ian M Campbell |
| Abstract |
Variant interpretation is a central challenge in genomic medicine. A recent study demonstrates the power of Bayesian statistical approaches to improve interpretation of variants in the context of specific genes and syndromes. Such Bayesian approaches combine frequency (in the form of observed genetic variation in cases and controls) with biological annotations to determine a probability of pathogenicity. These Bayesian approaches complement other efforts to catalog human variation. See related Research; 10.1186/s13073-014-0120-4. |
X Demographics
The data shown below were collected from the profiles of 7 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 Kingdom | 3 | 43% |
| Germany | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 71% |
| Members of the public | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 22% |
| Researcher | 2 | 22% |
| Other | 2 | 22% |
| Student > Doctoral Student | 1 | 11% |
| Unknown | 2 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 22% |
| Computer Science | 2 | 22% |
| Agricultural and Biological Sciences | 2 | 22% |
| Medicine and Dentistry | 2 | 22% |
| Unknown | 1 | 11% |
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 02 February 2015.
All research outputs
#7,778,730
of 25,374,917 outputs
Outputs from Genome Medicine
#1,194
of 1,585 outputs
Outputs of similar age
#98,768
of 361,129 outputs
Outputs of similar age from Genome Medicine
#20
of 29 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one is in the 24th percentile – i.e., 24% 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 361,129 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 72% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.