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DeeplyEssential: a deep neural network for predicting essential genes in microbes

Overview of attention for article published in BMC Bioinformatics, September 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
50 Mendeley
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Title
DeeplyEssential: a deep neural network for predicting essential genes in microbes
Published in
BMC Bioinformatics, September 2020
DOI 10.1186/s12859-020-03688-y
Pubmed ID
Authors

Md Abid Hasan, Stefano Lonardi

Twitter Demographics

The data shown below were collected from the profiles of 10 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 9 18%
Student > Master 8 16%
Student > Bachelor 5 10%
Student > Doctoral Student 3 6%
Other 8 16%
Unknown 7 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 22%
Computer Science 11 22%
Agricultural and Biological Sciences 6 12%
Engineering 3 6%
Environmental Science 2 4%
Other 6 12%
Unknown 11 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 October 2020.
All research outputs
#5,781,740
of 19,069,422 outputs
Outputs from BMC Bioinformatics
#2,369
of 6,513 outputs
Outputs of similar age
#123,094
of 321,814 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 50 outputs
Altmetric has tracked 19,069,422 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 6,513 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 61% 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 321,814 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 61% of its contemporaries.
We're also able to compare this research output to 50 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 72% of its contemporaries.