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OMG: Open Molecule Generator

Overview of attention for article published in Journal of Cheminformatics, September 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 (#11 of 689)
  • High Attention Score compared to outputs of the same age (97th percentile)

Mentioned by

6 blogs
18 tweeters
1 Wikipedia page
1 Google+ user


58 Dimensions

Readers on

124 Mendeley
3 CiteULike
OMG: Open Molecule Generator
Published in
Journal of Cheminformatics, September 2012
DOI 10.1186/1758-2946-4-21
Pubmed ID

Julio E Peironcely, Miguel Rojas-Chertó, Davide Fichera, Theo Reijmers, Leon Coulier, Jean-Loup Faulon, Thomas Hankemeier


Computer Assisted Structure Elucidation has been used for decades to discover the chemical structure of unknown compounds. In this work we introduce the first open source structure generator, Open Molecule Generator (OMG), which for a given elemental composition produces all non-isomorphic chemical structures that match that elemental composition. Furthermore, this structure generator can accept as additional input one or multiple non-overlapping prescribed substructures to drastically reduce the number of possible chemical structures. Being open source allows for customization and future extension of its functionality. OMG relies on a modified version of the Canonical Augmentation Path, which grows intermediate chemical structures by adding bonds and checks that at each step only unique molecules are produced. In order to benchmark the tool, we generated chemical structures for the elemental formulas and substructures of different metabolites and compared the results with a commercially available structure generator. The results obtained, i.e. the number of molecules generated, were identical for elemental compositions having only C, O and H. For elemental compositions containing C, O, H, N, P and S, OMG produces all the chemically valid molecules while the other generator produces more, yet chemically impossible, molecules. The chemical completeness of the OMG results comes at the expense of being slower than the commercial generator. In addition to being open source, OMG clearly showed the added value of constraining the solution space by using multiple prescribed substructures as input. We expect this structure generator to be useful in many fields, but to be especially of great importance for metabolomics, where identifying unknown metabolites is still a major bottleneck.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 2%
Spain 2 2%
United States 2 2%
Netherlands 2 2%
India 2 2%
Brazil 2 2%
South Africa 1 <1%
Australia 1 <1%
United Kingdom 1 <1%
Other 4 3%
Unknown 104 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 28%
Student > Ph. D. Student 32 26%
Student > Master 9 7%
Other 7 6%
Student > Doctoral Student 7 6%
Other 23 19%
Unknown 11 9%
Readers by discipline Count As %
Chemistry 42 34%
Agricultural and Biological Sciences 21 17%
Computer Science 15 12%
Biochemistry, Genetics and Molecular Biology 12 10%
Engineering 4 3%
Other 14 11%
Unknown 16 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 51. 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 16 June 2020.
All research outputs
of 17,968,541 outputs
Outputs from Journal of Cheminformatics
of 689 outputs
Outputs of similar age
of 143,465 outputs
Outputs of similar age from Journal of Cheminformatics
of 1 outputs
Altmetric has tracked 17,968,541 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 689 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. 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 143,465 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 97% of its contemporaries.
We're also able to compare this research output to 1 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