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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Copy number variation genotyping using family information
|
|---|---|
| Published in |
BMC Bioinformatics, May 2013
|
| DOI | 10.1186/1471-2105-14-157 |
| Pubmed ID | |
| Authors |
Jen-hwa Chu, Angela Rogers, Iuliana Ionita-Laza, Katayoon Darvishi, Ryan E Mills, Charles Lee, Benjamin A Raby |
| Abstract |
In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies. |
X Demographics
The data shown below were collected from the profiles of 8 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 | 2 | 25% |
| United Kingdom | 1 | 13% |
| Spain | 1 | 13% |
| Norway | 1 | 13% |
| France | 1 | 13% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 3 | 38% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Denmark | 1 | 2% |
| Singapore | 1 | 2% |
| Unknown | 49 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 23% |
| Student > Ph. D. Student | 10 | 19% |
| Student > Bachelor | 7 | 13% |
| Professor > Associate Professor | 4 | 8% |
| Student > Master | 4 | 8% |
| Other | 9 | 17% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 33% |
| Biochemistry, Genetics and Molecular Biology | 11 | 21% |
| Computer Science | 8 | 15% |
| Medicine and Dentistry | 6 | 12% |
| Mathematics | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 7 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 14 May 2013.
All research outputs
#7,174,980
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,657
of 7,454 outputs
Outputs of similar age
#58,649
of 195,592 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 124 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 63% 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 195,592 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 69% of its contemporaries.
We're also able to compare this research output to 124 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.