| Title |
Predicting variant deleteriousness in non-human species: applying the CADD approach in mouse
|
|---|---|
| Published in |
BMC Bioinformatics, October 2018
|
| DOI | 10.1186/s12859-018-2337-5 |
| Pubmed ID | |
| Authors |
Christian Groß, Dick de Ridder, Marcel Reinders |
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 Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 19% |
| Student > Master | 4 | 15% |
| Other | 2 | 8% |
| Student > Bachelor | 2 | 8% |
| Researcher | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 9 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Agricultural and Biological Sciences | 4 | 15% |
| Medicine and Dentistry | 3 | 12% |
| Nursing and Health Professions | 1 | 4% |
| Environmental Science | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 10 | 38% |
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 15 October 2018.
All research outputs
#13,514,576
of 23,316,003 outputs
Outputs from BMC Bioinformatics
#4,092
of 7,384 outputs
Outputs of similar age
#170,572
of 347,503 outputs
Outputs of similar age from BMC Bioinformatics
#72
of 122 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,384 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 42nd percentile – i.e., 42% 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 347,503 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.