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Comparative evaluation of open source software for mapping between metabolite identifiers in metabolic network reconstructions: application to Recon 2

Overview of attention for article published in Journal of Cheminformatics, January 2014
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Citations

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23 Dimensions

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78 Mendeley
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Title
Comparative evaluation of open source software for mapping between metabolite identifiers in metabolic network reconstructions: application to Recon 2
Published in
Journal of Cheminformatics, January 2014
DOI 10.1186/1758-2946-6-2
Pubmed ID
Authors

Hulda S Haraldsdóttir, Ines Thiele, Ronan MT Fleming

Abstract

An important step in the reconstruction of a metabolic network is annotation of metabolites. Metabolites are generally annotated with various database or structure based identifiers. Metabolite annotations in metabolic reconstructions may be incorrect or incomplete and thus need to be updated prior to their use. Genome-scale metabolic reconstructions generally include hundreds of metabolites. Manually updating annotations is therefore highly laborious. This prompted us to look for open-source software applications that could facilitate automatic updating of annotations by mapping between available metabolite identifiers. We identified three applications developed for the metabolomics and chemical informatics communities as potential solutions. The applications were MetMask, the Chemical Translation System, and UniChem. The first implements a "metabolite masking" strategy for mapping between identifiers whereas the latter two implement different versions of an InChI based strategy. Here we evaluated the suitability of these applications for the task of mapping between metabolite identifiers in genome-scale metabolic reconstructions. We applied the best suited application to updating identifiers in Recon 2, the latest reconstruction of human metabolism.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 4%
Colombia 1 1%
Netherlands 1 1%
Brazil 1 1%
Singapore 1 1%
China 1 1%
Unknown 70 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 31%
Researcher 17 22%
Student > Master 13 17%
Other 4 5%
Student > Postgraduate 3 4%
Other 11 14%
Unknown 6 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 40%
Biochemistry, Genetics and Molecular Biology 16 21%
Computer Science 9 12%
Engineering 3 4%
Chemistry 3 4%
Other 7 9%
Unknown 9 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 May 2015.
All research outputs
#15,207,446
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#755
of 891 outputs
Outputs of similar age
#181,547
of 316,488 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 11 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.