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The Molecule Cloud - compact visualization of large collections of molecules

Overview of attention for article published in Journal of Cheminformatics, July 2012
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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 (#42 of 494)
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

blogs
2 blogs
twitter
17 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
77 Mendeley
citeulike
2 CiteULike
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Title
The Molecule Cloud - compact visualization of large collections of molecules
Published in
Journal of Cheminformatics, July 2012
DOI 10.1186/1758-2946-4-12
Pubmed ID
Authors

Peter Ertl, Bernhard Rohde

Abstract

Analysis and visualization of large collections of molecules is one of the most frequent challenges cheminformatics experts in pharmaceutical industry are facing. Various sophisticated methods are available to perform this task, including clustering, dimensionality reduction or scaffold frequency analysis. In any case, however, viewing and analyzing large tables with molecular structures is necessary. We present a new visualization technique, providing basic information about the composition of molecular data sets at a single glance.

Twitter Demographics

The data shown below were collected from the profiles of 17 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 5%
United States 4 5%
Bulgaria 1 1%
Italy 1 1%
France 1 1%
Czechia 1 1%
United Kingdom 1 1%
Mexico 1 1%
Brazil 1 1%
Other 0 0%
Unknown 62 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 43%
Student > Ph. D. Student 16 21%
Professor > Associate Professor 6 8%
Student > Master 6 8%
Student > Bachelor 4 5%
Other 9 12%
Unknown 3 4%
Readers by discipline Count As %
Chemistry 31 40%
Computer Science 14 18%
Agricultural and Biological Sciences 10 13%
Biochemistry, Genetics and Molecular Biology 6 8%
Medicine and Dentistry 3 4%
Other 8 10%
Unknown 5 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 10 June 2013.
All research outputs
#558,647
of 12,434,464 outputs
Outputs from Journal of Cheminformatics
#42
of 494 outputs
Outputs of similar age
#4,893
of 119,501 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 4 outputs
Altmetric has tracked 12,434,464 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 494 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has done particularly well, scoring higher than 91% 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 119,501 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 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