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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of LDL cholesterol response to statin using transcriptomic and genetic variation
|
|---|---|
| Published in |
Genome Biology, September 2014
|
| DOI | 10.1186/s13059-014-0460-9 |
| Pubmed ID | |
| Authors |
Kyungpil Kim, Eugene Bolotin, Elizabeth Theusch, Haiyan Huang, Marisa W Medina, Ronald M Krauss |
| Abstract |
Statins are widely prescribed for lowering LDL-cholesterol (LDLC) levels and risk of cardiovascular disease. There is, however, substantial inter-individual variation in the magnitude of statin-induced LDLC reduction. To date, analysis of individual DNA sequence variants has explained only a small proportion of this variability. The present study was aimed at assessing whether transcriptomic analyses could be used to identify additional genetic contributions to inter-individual differences in statin efficacy. |
X Demographics
The data shown below were collected from the profiles of 25 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 | 20% |
| United Kingdom | 3 | 12% |
| France | 2 | 8% |
| Canada | 1 | 4% |
| Unknown | 14 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 56% |
| Members of the public | 9 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 65 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 21% |
| Student > Ph. D. Student | 13 | 19% |
| Student > Master | 9 | 13% |
| Student > Bachelor | 6 | 9% |
| Other | 5 | 7% |
| Other | 14 | 21% |
| Unknown | 6 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 24% |
| Medicine and Dentistry | 12 | 18% |
| Agricultural and Biological Sciences | 12 | 18% |
| Computer Science | 7 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 7 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 35. 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 May 2022.
All research outputs
#1,132,957
of 25,373,627 outputs
Outputs from Genome Biology
#838
of 4,467 outputs
Outputs of similar age
#12,100
of 264,647 outputs
Outputs of similar age from Genome Biology
#10
of 105 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% 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 has done well, scoring higher than 81% 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 264,647 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 105 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 90% of its contemporaries.