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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
  • Among the highest-scoring outputs from this source (#33 of 588)
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

news
2 news outlets
blogs
2 blogs
twitter
4 tweeters

Citations

dimensions_citation
127 Dimensions

Readers on

mendeley
279 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

Abstract

A method to estimate ease of synthesis (synthetic accessibility) of drug-like molecules is needed in many areas of the drug discovery process. The development and validation of such a method that is able to characterize molecule synthetic accessibility as a score between 1 (easy to make) and 10 (very difficult to make) is described in this article.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 279 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%
Belgium 1 <1%
Czechia 1 <1%
Romania 1 <1%
Spain 1 <1%
Japan 1 <1%
Other 2 <1%
Unknown 259 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 83 30%
Student > Ph. D. Student 49 18%
Student > Master 42 15%
Other 25 9%
Student > Bachelor 24 9%
Other 26 9%
Unknown 30 11%
Readers by discipline Count As %
Chemistry 122 44%
Computer Science 33 12%
Agricultural and Biological Sciences 22 8%
Biochemistry, Genetics and Molecular Biology 17 6%
Pharmacology, Toxicology and Pharmaceutical Science 13 5%
Other 33 12%
Unknown 39 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 30 March 2020.
All research outputs
#643,229
of 14,559,097 outputs
Outputs from Journal of Cheminformatics
#33
of 588 outputs
Outputs of similar age
#6,804
of 150,618 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 3 outputs
Altmetric has tracked 14,559,097 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 588 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has done particularly well, scoring higher than 94% 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 150,618 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 95% of its contemporaries.
We're also able to compare this research output to 3 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