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De Novo Drug Design Using Transformer-Based Machine Translation and Reinforcement Learning of an Adaptive Monte Carlo Tree Search

Overview of attention for article published in Pharmaceuticals, January 2024
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#41 of 3,968)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
17 news outlets
blogs
1 blog
twitter
13 X users

Readers on

mendeley
2 Mendeley
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Title
De Novo Drug Design Using Transformer-Based Machine Translation and Reinforcement Learning of an Adaptive Monte Carlo Tree Search
Published in
Pharmaceuticals, January 2024
DOI 10.3390/ph17020161
Pubmed ID
Authors

Dony Ang, Cyril Rakovski, Hagop S. Atamian

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Student > Ph. D. Student 1 50%
Student > Master 1 50%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 2 100%
Unspecified 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 123. 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 19 February 2024.
All research outputs
#345,470
of 25,713,737 outputs
Outputs from Pharmaceuticals
#41
of 3,968 outputs
Outputs of similar age
#4,989
of 345,348 outputs
Outputs of similar age from Pharmaceuticals
#1
of 113 outputs
Altmetric has tracked 25,713,737 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,968 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 98% 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 345,348 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 98% of its contemporaries.
We're also able to compare this research output to 113 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 99% of its contemporaries.