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Deep learning enables rapid identification of potent DDR1 kinase inhibitors

Overview of attention for article published in Nature Biotechnology, September 2019
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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 (#6 of 7,016)
  • 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)

Citations

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54 Dimensions

Readers on

mendeley
587 Mendeley
Title
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
Published in
Nature Biotechnology, September 2019
DOI 10.1038/s41587-019-0224-x
Pubmed ID
Authors

Alex Zhavoronkov, Yan A. Ivanenkov, Alex Aliper, Mark S. Veselov, Vladimir A. Aladinskiy, Anastasiya V. Aladinskaya, Victor A. Terentiev, Daniil A. Polykovskiy, Maksim D. Kuznetsov, Arip Asadulaev, Yury Volkov, Artem Zholus, Rim R. Shayakhmetov, Alexander Zhebrak, Lidiya I. Minaeva, Bogdan A. Zagribelnyy, Lennart H. Lee, Richard Soll, David Madge, Li Xing, Tao Guo, Alán Aspuru-Guzik

Twitter Demographics

The data shown below were collected from the profiles of 1,693 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 587 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 587 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 155 26%
Student > Ph. D. Student 120 20%
Student > Master 64 11%
Student > Bachelor 53 9%
Other 32 5%
Other 67 11%
Unknown 96 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 110 19%
Chemistry 98 17%
Computer Science 71 12%
Agricultural and Biological Sciences 51 9%
Pharmacology, Toxicology and Pharmaceutical Science 29 5%
Other 104 18%
Unknown 124 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1543. 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 15 June 2020.
All research outputs
#2,361
of 15,381,475 outputs
Outputs from Nature Biotechnology
#6
of 7,016 outputs
Outputs of similar age
#76
of 262,474 outputs
Outputs of similar age from Nature Biotechnology
#1
of 80 outputs
Altmetric has tracked 15,381,475 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 7,016 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.0. 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 262,474 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 80 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.