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Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions

Overview of attention for article published in PLoS Computational Biology, September 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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9 X users

Citations

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2 Dimensions

Readers on

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38 Mendeley
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3 CiteULike
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Title
Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions
Published in
PLoS Computational Biology, September 2015
DOI 10.1371/journal.pcbi.1004434
Pubmed ID
Authors

Claudio Altafini, Giuseppe Facchetti

Abstract

In simple organisms like E.coli, the metabolic response to an external perturbation passes through a transient phase in which the activation of a number of latent pathways can guarantee survival at the expenses of growth. Growth is gradually recovered as the organism adapts to the new condition. This adaptation can be modeled as a process of repeated metabolic adjustments obtained through the resilencings of the non-essential metabolic reactions, using growth rate as selection probability for the phenotypes obtained. The resulting metabolic adaptation process tends naturally to steer the metabolic fluxes towards high growth phenotypes. Quite remarkably, when applied to the central carbon metabolism of E.coli, it follows that nearly all flux distributions converge to the flux vector representing optimal growth, i.e., the solution of the biomass optimization problem turns out to be the dominant attractor of the metabolic adaptation process.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Israel 1 3%
Singapore 1 3%
Japan 1 3%
United States 1 3%
Unknown 33 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 39%
Student > Ph. D. Student 8 21%
Student > Master 5 13%
Professor 2 5%
Other 2 5%
Other 1 3%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 45%
Biochemistry, Genetics and Molecular Biology 4 11%
Computer Science 3 8%
Engineering 2 5%
Environmental Science 1 3%
Other 0 0%
Unknown 11 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 02 October 2015.
All research outputs
#7,205,295
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#4,893
of 8,960 outputs
Outputs of similar age
#78,169
of 277,644 outputs
Outputs of similar age from PLoS Computational Biology
#88
of 147 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 44th percentile – i.e., 44% 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 277,644 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.