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A Combinatorial Algorithm for Microbial Consortia Synthetic Design

Overview of attention for article published in Scientific Reports, July 2016
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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 (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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1 blog
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Citations

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25 Dimensions

Readers on

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118 Mendeley
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1 CiteULike
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Title
A Combinatorial Algorithm for Microbial Consortia Synthetic Design
Published in
Scientific Reports, July 2016
DOI 10.1038/srep29182
Pubmed ID
Authors

Alice Julien-Laferrière, Laurent Bulteau, Delphine Parrot, Alberto Marchetti-Spaccamela, Leen Stougie, Susana Vinga, Arnaud Mary, Marie-France Sagot

Abstract

Synthetic biology has boomed since the early 2000s when it started being shown that it was possible to efficiently synthetize compounds of interest in a much more rapid and effective way by using other organisms than those naturally producing them. However, to thus engineer a single organism, often a microbe, to optimise one or a collection of metabolic tasks may lead to difficulties when attempting to obtain a production system that is efficient, or to avoid toxic effects for the recruited microorganism. The idea of using instead a microbial consortium has thus started being developed in the last decade. This was motivated by the fact that such consortia may perform more complicated functions than could single populations and be more robust to environmental fluctuations. Success is however not always guaranteed. In particular, establishing which consortium is best for the production of a given compound or set thereof remains a great challenge. This is the problem we address in this paper. We thus introduce an initial model and a method that enable to propose a consortium to synthetically produce compounds that are either exogenous to it, or are endogenous but where interaction among the species in the consortium could improve the production line.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 <1%
United Kingdom 1 <1%
China 1 <1%
Unknown 115 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 30%
Student > Ph. D. Student 31 26%
Student > Master 8 7%
Student > Bachelor 7 6%
Student > Doctoral Student 6 5%
Other 14 12%
Unknown 17 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 27%
Biochemistry, Genetics and Molecular Biology 18 15%
Environmental Science 12 10%
Engineering 9 8%
Immunology and Microbiology 6 5%
Other 18 15%
Unknown 23 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 June 2018.
All research outputs
#3,997,455
of 24,885,505 outputs
Outputs from Scientific Reports
#32,033
of 136,320 outputs
Outputs of similar age
#66,845
of 362,287 outputs
Outputs of similar age from Scientific Reports
#864
of 3,681 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 136,320 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. 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 362,287 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 81% of its contemporaries.
We're also able to compare this research output to 3,681 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.