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GSA: an independent development algorithm for calling copy number and detecting homologous recombination deficiency (HRD) from target capture sequencing

Overview of attention for article published in BMC Bioinformatics, November 2021
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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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
twitter
11 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
13 Mendeley
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Title
GSA: an independent development algorithm for calling copy number and detecting homologous recombination deficiency (HRD) from target capture sequencing
Published in
BMC Bioinformatics, November 2021
DOI 10.1186/s12859-021-04487-9
Pubmed ID
Authors

Dongju Chen, Minghui Shao, Pei Meng, Chunli Wang, Qi Li, Yuhang Cai, Chengcheng Song, Xi Wang, Taiping Shi

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 54%
Student > Bachelor 1 8%
Student > Master 1 8%
Unknown 4 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 31%
Agricultural and Biological Sciences 2 15%
Computer Science 1 8%
Sports and Recreations 1 8%
Chemistry 1 8%
Other 0 0%
Unknown 4 31%

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 19 January 2022.
All research outputs
#2,730,233
of 21,604,059 outputs
Outputs from BMC Bioinformatics
#992
of 6,984 outputs
Outputs of similar age
#80,643
of 480,220 outputs
Outputs of similar age from BMC Bioinformatics
#93
of 557 outputs
Altmetric has tracked 21,604,059 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 6,984 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 well, scoring higher than 85% 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 480,220 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 83% of its contemporaries.
We're also able to compare this research output to 557 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.