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Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

Overview of attention for article published in Nature Chemical Biology, May 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#1 of 3,571)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Readers on

mendeley
288 Mendeley
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Title
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
Published in
Nature Chemical Biology, May 2023
DOI 10.1038/s41589-023-01349-8
Pubmed ID
Authors

Gary Liu, Denise B. Catacutan, Khushi Rathod, Kyle Swanson, Wengong Jin, Jody C. Mohammed, Anush Chiappino-Pepe, Saad A. Syed, Meghan Fragis, Kenneth Rachwalski, Jakob Magolan, Michael G. Surette, Brian K. Coombes, Tommi Jaakkola, Regina Barzilay, James J. Collins, Jonathan M. Stokes

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 549 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 288 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 288 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 16%
Researcher 42 15%
Student > Bachelor 27 9%
Student > Master 17 6%
Other 10 3%
Other 33 11%
Unknown 114 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 46 16%
Chemistry 30 10%
Agricultural and Biological Sciences 22 8%
Computer Science 11 4%
Immunology and Microbiology 10 3%
Other 46 16%
Unknown 123 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1483. 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 23 August 2024.
All research outputs
#8,633
of 26,639,477 outputs
Outputs from Nature Chemical Biology
#1
of 3,571 outputs
Outputs of similar age
#243
of 402,726 outputs
Outputs of similar age from Nature Chemical Biology
#1
of 68 outputs
Altmetric has tracked 26,639,477 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,571 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has done particularly well, scoring higher than 99% 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 402,726 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.