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Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection

Overview of attention for article published in Genome Biology, November 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)

Mentioned by

twitter
19 X users

Readers on

mendeley
94 Mendeley
citeulike
1 CiteULike
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Title
Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection
Published in
Genome Biology, November 2018
DOI 10.1186/s13059-018-1539-5
Pubmed ID
Authors

Anna Y. Lee, Adam D. Ewing, Kyle Ellrott, Yin Hu, Kathleen E. Houlahan, J. Christopher Bare, Shadrielle Melijah G. Espiritu, Vincent Huang, Kristen Dang, Zechen Chong, Cristian Caloian, Takafumi N. Yamaguchi, Michael R. Kellen, Ken Chen, Thea C. Norman, Stephen H. Friend, Justin Guinney, Gustavo Stolovitzky, David Haussler, Adam A. Margolin, Joshua M. Stuart, Paul C. Boutros

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 20%
Student > Ph. D. Student 12 13%
Student > Master 8 9%
Student > Bachelor 8 9%
Student > Postgraduate 7 7%
Other 21 22%
Unknown 19 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 29 31%
Medicine and Dentistry 12 13%
Agricultural and Biological Sciences 12 13%
Computer Science 8 9%
Engineering 5 5%
Other 8 9%
Unknown 20 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 27 November 2018.
All research outputs
#3,270,569
of 25,385,509 outputs
Outputs from Genome Biology
#2,362
of 4,468 outputs
Outputs of similar age
#65,999
of 365,313 outputs
Outputs of similar age from Genome Biology
#63
of 85 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 365,313 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 81% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.