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Mimoza: web-based semantic zooming and navigation in metabolic networks

Overview of attention for article published in BMC Systems Biology, February 2015
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1 X user

Citations

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Title
Mimoza: web-based semantic zooming and navigation in metabolic networks
Published in
BMC Systems Biology, February 2015
DOI 10.1186/s12918-015-0151-5
Pubmed ID
Authors

Anna Zhukova, David J Sherman

Abstract

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner CONCLUSIONS: Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 3%
Brazil 1 3%
United Kingdom 1 3%
Singapore 1 3%
Russia 1 3%
United States 1 3%
Unknown 32 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 42%
Student > Bachelor 5 13%
Student > Ph. D. Student 5 13%
Professor > Associate Professor 3 8%
Student > Doctoral Student 2 5%
Other 4 11%
Unknown 3 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 37%
Computer Science 6 16%
Biochemistry, Genetics and Molecular Biology 4 11%
Engineering 4 11%
Chemistry 1 3%
Other 1 3%
Unknown 8 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 March 2015.
All research outputs
#18,836,331
of 23,344,526 outputs
Outputs from BMC Systems Biology
#838
of 1,143 outputs
Outputs of similar age
#187,034
of 256,492 outputs
Outputs of similar age from BMC Systems Biology
#17
of 21 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,143 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 256,492 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.