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NanoVar: accurate characterization of patients’ genomic structural variants using low-depth nanopore sequencing

Overview of attention for article published in Genome Biology, March 2020
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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 (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
45 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
125 Mendeley
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Title
NanoVar: accurate characterization of patients’ genomic structural variants using low-depth nanopore sequencing
Published in
Genome Biology, March 2020
DOI 10.1186/s13059-020-01968-7
Pubmed ID
Authors

Cheng Yong Tham, Roberto Tirado-Magallanes, Yufen Goh, Melissa J. Fullwood, Bryan T.H. Koh, Wilson Wang, Chin Hin Ng, Wee Joo Chng, Alexandre Thiery, Daniel G. Tenen, Touati Benoukraf

X Demographics

X Demographics

The data shown below were collected from the profiles of 45 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 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 125 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 18%
Student > Ph. D. Student 17 14%
Student > Bachelor 11 9%
Student > Doctoral Student 9 7%
Student > Master 8 6%
Other 22 18%
Unknown 36 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 40 32%
Agricultural and Biological Sciences 22 18%
Computer Science 8 6%
Medicine and Dentistry 3 2%
Nursing and Health Professions 2 2%
Other 10 8%
Unknown 40 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 November 2023.
All research outputs
#1,401,865
of 25,387,668 outputs
Outputs from Genome Biology
#1,114
of 4,470 outputs
Outputs of similar age
#34,413
of 384,883 outputs
Outputs of similar age from Genome Biology
#31
of 75 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 75% 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 384,883 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 91% of its contemporaries.
We're also able to compare this research output to 75 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 58% of its contemporaries.