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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 (75th percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
25 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

Hasan, Md Abid, Lonardi, Stefano

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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 24%
Student > Ph. D. Student 5 20%
Student > Bachelor 3 12%
Student > Master 3 12%
Student > Doctoral Student 2 8%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 7 28%
Agricultural and Biological Sciences 5 20%
Biochemistry, Genetics and Molecular Biology 3 12%
Environmental Science 2 8%
Psychology 1 4%
Other 2 8%
Unknown 5 20%

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
#5,249,469
of 17,405,806 outputs
Outputs from BMC Bioinformatics
#2,223
of 6,157 outputs
Outputs of similar age
#120,274
of 318,194 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 49 outputs
Altmetric has tracked 17,405,806 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 6,157 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 62% 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 318,194 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 49 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.