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Mixtures, metabolites, ionic liquids: a new measure to evaluate similarity between complex chemical systems

Overview of attention for article published in Journal of Cheminformatics, September 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
24 Mendeley
citeulike
1 CiteULike
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Title
Mixtures, metabolites, ionic liquids: a new measure to evaluate similarity between complex chemical systems
Published in
Journal of Cheminformatics, September 2016
DOI 10.1186/s13321-016-0159-x
Pubmed ID
Authors

Andrea Mauri, Davide Ballabio, Roberto Todeschini, Viviana Consonni

Abstract

This communication deals with the scientific problem of evaluating the similarity between two chemical systems, each described by a finite discrete set of elements/members, which are in turn p-dimensional vectors of chemical/biological descriptors. A variant of the Hausdorff measure, called Hausdorff-like similarity (Hs), is proposed aimed at taking into account information on all the elements present in the compared sets, information that is usually lost by the other measures.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 4%
Brazil 1 4%
Unknown 22 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Student > Master 5 21%
Other 4 17%
Researcher 4 17%
Student > Bachelor 1 4%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Chemistry 8 33%
Pharmacology, Toxicology and Pharmaceutical Science 3 13%
Agricultural and Biological Sciences 3 13%
Environmental Science 2 8%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 2 8%
Unknown 5 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 28 January 2020.
All research outputs
#3,684,648
of 22,889,074 outputs
Outputs from Journal of Cheminformatics
#361
of 838 outputs
Outputs of similar age
#62,096
of 321,009 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 23 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 838 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 56% 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 321,009 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.