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X Demographics
Mendeley readers
Attention Score in Context
Title |
Inferring copy number and genotype in tumour exome data
|
---|---|
Published in |
BMC Genomics, August 2014
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DOI | 10.1186/1471-2164-15-732 |
Pubmed ID | |
Authors |
Kaushalya C Amarasinghe, Jason Li, Sally M Hunter, Georgina L Ryland, Prue A Cowin, Ian G Campbell, Saman K Halgamuge |
Abstract |
Using whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequencing, however is predominantly used for variant detection and infrequently utilised for detection of somatic copy number variation. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 25% |
Australia | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
United Kingdom | 2 | 2% |
Netherlands | 1 | <1% |
Brazil | 1 | <1% |
Norway | 1 | <1% |
China | 1 | <1% |
Australia | 1 | <1% |
Unknown | 123 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 32 | 24% |
Researcher | 32 | 24% |
Student > Master | 20 | 15% |
Professor > Associate Professor | 8 | 6% |
Student > Bachelor | 6 | 5% |
Other | 18 | 14% |
Unknown | 17 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 44 | 33% |
Biochemistry, Genetics and Molecular Biology | 31 | 23% |
Medicine and Dentistry | 15 | 11% |
Computer Science | 9 | 7% |
Engineering | 4 | 3% |
Other | 8 | 6% |
Unknown | 22 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 January 2024.
All research outputs
#6,427,083
of 25,223,158 outputs
Outputs from BMC Genomics
#2,484
of 11,195 outputs
Outputs of similar age
#57,363
of 243,402 outputs
Outputs of similar age from BMC Genomics
#40
of 188 outputs
Altmetric has tracked 25,223,158 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 11,195 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 77% 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 243,402 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 188 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.