↓ Skip to main content

A Design Principle of Group-level Decision Making in Cell Populations

Overview of attention for article published in PLoS Computational Biology, June 2013
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
113 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A Design Principle of Group-level Decision Making in Cell Populations
Published in
PLoS Computational Biology, June 2013
DOI 10.1371/journal.pcbi.1003110
Pubmed ID
Authors

Koichi Fujimoto, Satoshi Sawai

Abstract

Populations of cells often switch states as a group to cope with environmental changes such as nutrient availability and cell density. Although the gene circuits that underlie the switches are well understood at the level of single cells, the ways in which such circuits work in concert among many cells to support group-level switches are not fully explored. Experimental studies of microbial quorum sensing show that group-level changes in cellular states occur in either a graded or an all-or-none fashion. Here, we show through numerical simulations and mathematical analysis that these behaviors generally originate from two distinct forms of bistability. The choice of bistability is uniquely determined by a dimensionless parameter that compares the synthesis and the transport of the inducing molecules. The role of the parameter is universal, such that it not only applies to the autoinducing circuits typically found in bacteria but also to the more complex gene circuits involved in transmembrane receptor signaling. Furthermore, in gene circuits with negative feedback, the same dimensionless parameter determines the coherence of group-level transitions from quiescence to a rhythmic state. The set of biochemical parameters in bacterial quorum-sensing circuits appear to be tuned so that the cells can use either type of transition. The design principle identified here serves as the basis for the analysis and control of cellular collective decision making.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Portugal 1 <1%
Germany 1 <1%
France 1 <1%
Netherlands 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 105 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 26%
Researcher 20 18%
Professor > Associate Professor 13 12%
Student > Bachelor 12 11%
Student > Master 7 6%
Other 18 16%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 42%
Biochemistry, Genetics and Molecular Biology 17 15%
Physics and Astronomy 8 7%
Engineering 7 6%
Computer Science 4 4%
Other 13 12%
Unknown 16 14%
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 18 July 2014.
All research outputs
#7,151,201
of 25,461,852 outputs
Outputs from PLoS Computational Biology
#4,834
of 8,981 outputs
Outputs of similar age
#57,504
of 209,079 outputs
Outputs of similar age from PLoS Computational Biology
#46
of 100 outputs
Altmetric has tracked 25,461,852 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 8,981 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 46th percentile – i.e., 46% 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 209,079 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 72% of its contemporaries.
We're also able to compare this research output to 100 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 53% of its contemporaries.