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Kinetic Memory Based on the Enzyme-Limited Competition

Overview of attention for article published in PLoS Computational Biology, August 2014
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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 (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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9 X users
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1 Google+ user

Citations

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12 Dimensions

Readers on

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23 Mendeley
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2 CiteULike
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Title
Kinetic Memory Based on the Enzyme-Limited Competition
Published in
PLoS Computational Biology, August 2014
DOI 10.1371/journal.pcbi.1003784
Pubmed ID
Authors

Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

Abstract

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed, including dynamic modifications of calcium-calmodulin kinase II and cAMP-response element-binding protein essential for synaptic plasticity.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 13%
Canada 1 4%
Unknown 19 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 43%
Researcher 3 13%
Student > Master 3 13%
Student > Bachelor 2 9%
Lecturer > Senior Lecturer 1 4%
Other 1 4%
Unknown 3 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 26%
Agricultural and Biological Sciences 6 26%
Physics and Astronomy 5 22%
Mathematics 2 9%
Social Sciences 1 4%
Other 0 0%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 12 December 2023.
All research outputs
#6,324,035
of 25,468,708 outputs
Outputs from PLoS Computational Biology
#4,271
of 8,983 outputs
Outputs of similar age
#55,604
of 243,894 outputs
Outputs of similar age from PLoS Computational Biology
#66
of 159 outputs
Altmetric has tracked 25,468,708 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,983 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 52% 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 243,894 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 77% of its contemporaries.
We're also able to compare this research output to 159 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 59% of its contemporaries.