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OptFlux: an open-source software platform for in silico metabolic engineering

Overview of attention for article published in BMC Systems Biology, April 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
2 tweeters
patent
2 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
304 Dimensions

Readers on

mendeley
592 Mendeley
citeulike
16 CiteULike
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Title
OptFlux: an open-source software platform for in silico metabolic engineering
Published in
BMC Systems Biology, April 2010
DOI 10.1186/1752-0509-4-45
Pubmed ID
Authors

Isabel Rocha, Paulo Maia, Pedro Evangelista, Paulo Vilaça, Simão Soares, José P Pinto, Jens Nielsen, Kiran R Patil, Eugénio C Ferreira, Miguel Rocha

Abstract

Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 592 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
United Kingdom 6 1%
France 5 <1%
Latvia 4 <1%
Portugal 4 <1%
Brazil 3 <1%
Switzerland 3 <1%
Colombia 2 <1%
Germany 2 <1%
Other 19 3%
Unknown 535 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 130 22%
Student > Master 116 20%
Researcher 108 18%
Student > Bachelor 54 9%
Student > Doctoral Student 30 5%
Other 89 15%
Unknown 65 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 246 42%
Biochemistry, Genetics and Molecular Biology 93 16%
Computer Science 53 9%
Engineering 52 9%
Chemistry 15 3%
Other 50 8%
Unknown 83 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 20 February 2018.
All research outputs
#2,682,738
of 22,661,413 outputs
Outputs from BMC Systems Biology
#73
of 1,142 outputs
Outputs of similar age
#10,406
of 93,716 outputs
Outputs of similar age from BMC Systems Biology
#2
of 25 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 93% 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 93,716 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 88% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.