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Title |
Copy number variation analysis in the context of electronic medical records and large-scale genomics consortium efforts
|
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Published in |
Frontiers in Genetics, March 2014
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DOI | 10.3389/fgene.2014.00051 |
Pubmed ID | |
Authors |
John J. Connolly, Joseph T. Glessner, Berta Almoguera, David R. Crosslin, Gail P. Jarvik, Patrick M. Sleiman, Hakon Hakonarson |
Abstract |
The goal of this paper is to review recent research on copy number variations (CNVs) and their association with complex and rare diseases. In the latter part of this paper, we focus on how large biorepositories such as the electronic medical record and genomics (eMERGE) consortium may be best leveraged to systematically mine for potentially pathogenic CNVs, and we end with a discussion of how such variants might be reported back for inclusion in electronic medical records as part of medical history. |
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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 1 | 20% |
United Kingdom | 1 | 20% |
India | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 40% |
Practitioners (doctors, other healthcare professionals) | 2 | 40% |
Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 2 | 4% |
Hong Kong | 1 | 2% |
Unknown | 48 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 27% |
Student > Master | 9 | 18% |
Student > Ph. D. Student | 9 | 18% |
Other | 3 | 6% |
Student > Doctoral Student | 2 | 4% |
Other | 4 | 8% |
Unknown | 10 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 14 | 27% |
Agricultural and Biological Sciences | 12 | 24% |
Medicine and Dentistry | 7 | 14% |
Computer Science | 3 | 6% |
Psychology | 1 | 2% |
Other | 3 | 6% |
Unknown | 11 | 22% |
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 29 March 2014.
All research outputs
#7,442,077
of 22,749,166 outputs
Outputs from Frontiers in Genetics
#2,425
of 11,758 outputs
Outputs of similar age
#80,688
of 242,903 outputs
Outputs of similar age from Frontiers in Genetics
#32
of 64 outputs
Altmetric has tracked 22,749,166 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 11,758 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 78% 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 242,903 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 64 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.