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Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

Overview of attention for article published in Journal of Cheminformatics, June 2009
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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 (#9 of 981)
  • High Attention Score compared to outputs of the same age (98th percentile)

Mentioned by

news
2 news outlets
blogs
4 blogs
twitter
11 X users
patent
6 patents
q&a
2 Q&A threads

Citations

dimensions_citation
879 Dimensions

Readers on

mendeley
842 Mendeley
citeulike
4 CiteULike
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Title
Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
Published in
Journal of Cheminformatics, June 2009
DOI 10.1186/1758-2946-1-8
Pubmed ID
Authors

Peter Ertl, Ansgar Schuffenhauer

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 842 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Germany 3 <1%
Indonesia 3 <1%
United Kingdom 3 <1%
Czechia 1 <1%
Belgium 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Romania 1 <1%
Other 2 <1%
Unknown 822 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 162 19%
Student > Ph. D. Student 121 14%
Student > Bachelor 99 12%
Student > Master 96 11%
Other 38 5%
Other 90 11%
Unknown 236 28%
Readers by discipline Count As %
Chemistry 247 29%
Biochemistry, Genetics and Molecular Biology 65 8%
Computer Science 56 7%
Pharmacology, Toxicology and Pharmaceutical Science 54 6%
Agricultural and Biological Sciences 41 5%
Other 114 14%
Unknown 265 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 58. 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 03 April 2023.
All research outputs
#752,144
of 25,761,363 outputs
Outputs from Journal of Cheminformatics
#9
of 981 outputs
Outputs of similar age
#1,898
of 124,549 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 4 outputs
Altmetric has tracked 25,761,363 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. 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 124,549 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them