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Mendeley readers
Attention Score in Context
| Title |
CNV-seq, a new method to detect copy number variation using high-throughput sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, March 2009
|
| DOI | 10.1186/1471-2105-10-80 |
| Pubmed ID | |
| Authors |
Chao Xie, Martti T Tammi |
| Abstract |
DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. |
Mendeley readers
The data shown below were compiled from readership statistics for 752 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 29 | 4% |
| United Kingdom | 13 | 2% |
| Brazil | 9 | 1% |
| Germany | 8 | 1% |
| France | 6 | <1% |
| Belgium | 4 | <1% |
| Netherlands | 4 | <1% |
| Italy | 3 | <1% |
| Switzerland | 3 | <1% |
| Other | 15 | 2% |
| Unknown | 658 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 223 | 30% |
| Student > Ph. D. Student | 162 | 22% |
| Student > Master | 73 | 10% |
| Student > Bachelor | 48 | 6% |
| Professor > Associate Professor | 42 | 6% |
| Other | 121 | 16% |
| Unknown | 83 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 416 | 55% |
| Biochemistry, Genetics and Molecular Biology | 119 | 16% |
| Computer Science | 43 | 6% |
| Medicine and Dentistry | 40 | 5% |
| Mathematics | 10 | 1% |
| Other | 31 | 4% |
| Unknown | 93 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 03 October 2023.
All research outputs
#2,171,700
of 23,575,346 outputs
Outputs from BMC Bioinformatics
#556
of 7,398 outputs
Outputs of similar age
#6,728
of 95,068 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 50 outputs
Altmetric has tracked 23,575,346 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,398 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 92% 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 95,068 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 92% of its contemporaries.
We're also able to compare this research output to 50 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 94% of its contemporaries.