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Attention Score in Context
Title |
Prioritizing causal disease genes using unbiased genomic features
|
---|---|
Published in |
Genome Biology, December 2014
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DOI | 10.1186/s13059-014-0534-8 |
Pubmed ID | |
Authors |
Rahul C Deo, Gabriel Musso, Murat Tasan, Paul Tang, Annie Poon, Christiana Yuan, Janine F Felix, Ramachandran S Vasan, Rameen Beroukhim, Teresa De Marco, Pui-Yan Kwok, Calum A MacRae, Frederick P Roth |
Abstract |
Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. |
X Demographics
The data shown below were collected from the profiles of 14 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 | 5 | 36% |
United Kingdom | 3 | 21% |
Germany | 2 | 14% |
Canada | 1 | 7% |
Switzerland | 1 | 7% |
Unknown | 2 | 14% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 8 | 57% |
Members of the public | 5 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 3% |
United Kingdom | 1 | <1% |
Taiwan | 1 | <1% |
South Africa | 1 | <1% |
Unknown | 139 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 35 | 24% |
Student > Ph. D. Student | 32 | 22% |
Student > Bachelor | 16 | 11% |
Professor > Associate Professor | 10 | 7% |
Student > Master | 10 | 7% |
Other | 21 | 14% |
Unknown | 23 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 39 | 27% |
Biochemistry, Genetics and Molecular Biology | 29 | 20% |
Medicine and Dentistry | 24 | 16% |
Computer Science | 12 | 8% |
Engineering | 5 | 3% |
Other | 13 | 9% |
Unknown | 25 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 March 2015.
All research outputs
#4,592,553
of 25,371,288 outputs
Outputs from Genome Biology
#2,726
of 4,467 outputs
Outputs of similar age
#59,880
of 368,274 outputs
Outputs of similar age from Genome Biology
#66
of 101 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 38th percentile – i.e., 38% 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 368,274 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 83% of its contemporaries.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.