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FASIMU: flexible software for flux-balance computation series in large metabolic networks

Overview of attention for article published in BMC Bioinformatics, January 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
1 tweeter
wikipedia
1 Wikipedia page

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
149 Mendeley
citeulike
2 CiteULike
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Title
FASIMU: flexible software for flux-balance computation series in large metabolic networks
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-28
Pubmed ID
Authors

Andreas Hoppe, Sabrina Hoffmann, Andreas Gerasch, Christoph Gille, Hermann-Georg Holzhütter

Abstract

Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.

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

Geographical breakdown

Country Count As %
United Kingdom 4 3%
United States 4 3%
Latvia 3 2%
Colombia 2 1%
Austria 2 1%
Germany 2 1%
Iran, Islamic Republic of 2 1%
Singapore 1 <1%
Canada 1 <1%
Other 4 3%
Unknown 124 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 23%
Student > Ph. D. Student 32 21%
Student > Master 27 18%
Professor > Associate Professor 18 12%
Student > Bachelor 9 6%
Other 23 15%
Unknown 5 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 58%
Computer Science 19 13%
Biochemistry, Genetics and Molecular Biology 12 8%
Engineering 11 7%
Medicine and Dentistry 2 1%
Other 10 7%
Unknown 8 5%

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 01 March 2017.
All research outputs
#2,085,732
of 9,134,189 outputs
Outputs from BMC Bioinformatics
#1,219
of 3,893 outputs
Outputs of similar age
#63,032
of 257,733 outputs
Outputs of similar age from BMC Bioinformatics
#40
of 155 outputs
Altmetric has tracked 9,134,189 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,893 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 67% 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 257,733 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 155 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 72% of its contemporaries.