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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve
|
|---|---|
| Published in |
BMC Medical Genomics, September 2014
|
| DOI | 10.1186/1755-8794-7-56 |
| Pubmed ID | |
| Authors |
Elizabeth M Bonachea, Gloria Zender, Peter White, Don Corsmeier, David Newsom, Sara Fitzgerald-Butt, Vidu Garg, Kim L McBride |
| Abstract |
Bicuspid aortic valve (BAV) is the most common type of congenital heart disease with a population prevalence of 1-2%. While BAV is known to be highly heritable, mutations in single genes (such as GATA5 and NOTCH1) have been reported in few human BAV cases. Traditional gene sequencing methods are time and labor intensive, while next-generation high throughput sequencing remains costly for large patient cohorts and requires extensive bioinformatics processing. Here we describe an approach to targeted multi-gene sequencing with combinatorial pooling of samples from BAV patients. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 20% |
| United States | 1 | 20% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| United States | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 53 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 27% |
| Researcher | 8 | 14% |
| Student > Master | 8 | 14% |
| Other | 3 | 5% |
| Student > Doctoral Student | 3 | 5% |
| Other | 12 | 21% |
| Unknown | 7 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 29% |
| Agricultural and Biological Sciences | 11 | 20% |
| Biochemistry, Genetics and Molecular Biology | 9 | 16% |
| Unspecified | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 4 | 7% |
| Unknown | 12 | 21% |
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 04 March 2015.
All research outputs
#13,314,015
of 23,975,876 outputs
Outputs from BMC Medical Genomics
#440
of 1,278 outputs
Outputs of similar age
#114,303
of 255,486 outputs
Outputs of similar age from BMC Medical Genomics
#6
of 13 outputs
Altmetric has tracked 23,975,876 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,278 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 65% 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 255,486 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 54% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.