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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning
|
|---|---|
| Published in |
Genome Medicine, October 2022
|
| DOI | 10.1186/s13073-022-01120-z |
| Pubmed ID | |
| Authors |
Chang Li, Degui Zhi, Kai Wang, Xiaoming Liu |
X Demographics
The data shown below were collected from the profiles of 12 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 | 25% |
| China | 1 | 8% |
| Thailand | 1 | 8% |
| India | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 58% |
| Members of the public | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 18 | 25% |
| Student > Master | 7 | 10% |
| Researcher | 4 | 6% |
| Student > Ph. D. Student | 4 | 6% |
| Student > Bachelor | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 25 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 18 | 25% |
| Biochemistry, Genetics and Molecular Biology | 17 | 24% |
| Medicine and Dentistry | 4 | 6% |
| Agricultural and Biological Sciences | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Other | 4 | 6% |
| Unknown | 26 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 11 October 2022.
All research outputs
#6,855,527
of 24,846,849 outputs
Outputs from Genome Medicine
#1,106
of 1,529 outputs
Outputs of similar age
#125,428
of 433,157 outputs
Outputs of similar age from Genome Medicine
#26
of 33 outputs
Altmetric has tracked 24,846,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,529 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one is in the 27th percentile – i.e., 27% 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 433,157 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 70% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.