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Inferring copy number and genotype in tumour exome data

Overview of attention for article published in BMC Genomics, August 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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1 patent

Citations

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98 Dimensions

Readers on

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133 Mendeley
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4 CiteULike
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Title
Inferring copy number and genotype in tumour exome data
Published in
BMC Genomics, August 2014
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

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.
Mendeley readers

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

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.