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HELLO: improved neural network architectures and methodologies for small variant calling

Overview of attention for article published in BMC Bioinformatics, August 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
9 tweeters

Readers on

mendeley
9 Mendeley
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Title
HELLO: improved neural network architectures and methodologies for small variant calling
Published in
BMC Bioinformatics, August 2021
DOI 10.1186/s12859-021-04311-4
Pubmed ID
Authors

Anand Ramachandran, Steven S. Lumetta, Eric W. Klee, Deming Chen

Twitter Demographics

The data shown below were collected from the profiles of 9 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Professor > Associate Professor 1 11%
Unspecified 1 11%
Researcher 1 11%
Other 1 11%
Other 0 0%
Unknown 3 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 22%
Biochemistry, Genetics and Molecular Biology 2 22%
Computer Science 1 11%
Unspecified 1 11%
Unknown 3 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 September 2021.
All research outputs
#10,597,695
of 19,164,538 outputs
Outputs from BMC Bioinformatics
#3,355
of 6,527 outputs
Outputs of similar age
#135,364
of 331,147 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 10 outputs
Altmetric has tracked 19,164,538 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,527 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 46th percentile – i.e., 46% 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 331,147 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.