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A proof for loop-law constraints in stoichiometric metabolic networks

Overview of attention for article published in BMC Systems Biology, November 2012
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Mentioned by

twitter
3 tweeters

Citations

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18 Dimensions

Readers on

mendeley
84 Mendeley
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3 CiteULike
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Title
A proof for loop-law constraints in stoichiometric metabolic networks
Published in
BMC Systems Biology, November 2012
DOI 10.1186/1752-0509-6-140
Pubmed ID
Authors

Elad Noor, Elad Noor, Nathan E Lewis, Ron Milo

Abstract

Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well.

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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 4%
United Kingdom 1 1%
Switzerland 1 1%
France 1 1%
Portugal 1 1%
Singapore 1 1%
Iran, Islamic Republic of 1 1%
Denmark 1 1%
Japan 1 1%
Other 1 1%
Unknown 72 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 27%
Researcher 23 27%
Professor > Associate Professor 8 10%
Student > Master 8 10%
Student > Bachelor 5 6%
Other 9 11%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 37%
Biochemistry, Genetics and Molecular Biology 14 17%
Engineering 7 8%
Mathematics 6 7%
Computer Science 4 5%
Other 9 11%
Unknown 13 15%

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 13 November 2012.
All research outputs
#10,995,325
of 18,245,787 outputs
Outputs from BMC Systems Biology
#506
of 1,116 outputs
Outputs of similar age
#87,583
of 162,115 outputs
Outputs of similar age from BMC Systems Biology
#6
of 20 outputs
Altmetric has tracked 18,245,787 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,116 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 49th percentile – i.e., 49% 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 162,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 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 50% of its contemporaries.