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Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

Overview of attention for article published in BMC Systems Biology, January 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
1 tweeter
patent
1 patent

Citations

dimensions_citation
49 Dimensions

Readers on

mendeley
121 Mendeley
citeulike
1 CiteULike
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Title
Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico
Published in
BMC Systems Biology, January 2012
DOI 10.1186/1752-0509-6-42
Pubmed ID
Authors

Michael J McAnulty, Jiun Y Yen, Benjamin G Freedman, Ryan S Senger

Abstract

Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Denmark 2 2%
France 1 <1%
Thailand 1 <1%
Brazil 1 <1%
Iran, Islamic Republic of 1 <1%
Latvia 1 <1%
Colombia 1 <1%
Singapore 1 <1%
Other 1 <1%
Unknown 108 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 33%
Researcher 33 27%
Student > Master 15 12%
Professor > Associate Professor 9 7%
Student > Postgraduate 6 5%
Other 18 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 65 54%
Biochemistry, Genetics and Molecular Biology 19 16%
Engineering 12 10%
Unspecified 11 9%
Computer Science 5 4%
Other 9 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 March 2016.
All research outputs
#2,403,727
of 9,375,258 outputs
Outputs from BMC Systems Biology
#208
of 916 outputs
Outputs of similar age
#23,959
of 98,929 outputs
Outputs of similar age from BMC Systems Biology
#6
of 29 outputs
Altmetric has tracked 9,375,258 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 916 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 76% 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 98,929 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.