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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 (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
7 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
57 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

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 21%
Student > Master 9 16%
Researcher 8 14%
Student > Bachelor 4 7%
Student > Doctoral Student 3 5%
Other 9 16%
Unknown 12 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 19%
Computer Science 11 19%
Agricultural and Biological Sciences 6 11%
Engineering 3 5%
Environmental Science 2 4%
Other 8 14%
Unknown 16 28%
Attention Score in Context

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 02 October 2020.
All research outputs
#13,242,166
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#3,862
of 7,387 outputs
Outputs of similar age
#191,656
of 412,222 outputs
Outputs of similar age from BMC Bioinformatics
#82
of 168 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 412,222 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 52% of its contemporaries.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.