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Emergence of microbial networks as response to hostile environments

Overview of attention for article published in Frontiers in Microbiology, August 2014
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Emergence of microbial networks as response to hostile environments
Published in
Frontiers in Microbiology, August 2014
DOI 10.3389/fmicb.2014.00407
Pubmed ID
Authors

Dario Madeo, Luis R. Comolli, Chiara Mocenni

Abstract

The majority of microorganisms live in complex communities under varying conditions. One pivotal question in evolutionary biology is the emergence of cooperative traits and their sustainment in altered environments or in the presence of free-riders. Co-occurrence patterns in the spatial distribution of biofilms can help define species' identities, and systems biology tools are revealing networks of interacting microorganisms. However, networks of inter-dependencies involving micro-organisms in the planktonic phase may be just as important, with the added complexity that they are not bounded in space. An integrated approach linking imaging, "Omics" and modeling has the potential to enable new hypothesis and working models. In order to understand how cooperation can emerge and be maintained without abilities like memory or recognition we use evolutionary game theory as the natural framework to model cell-cell interactions arising from evolutive decisions. We consider a finite population distributed in a spatial domain (biofilm), and divided into two interacting classes with different traits. This interaction can be weighted by distance, and produces physical connections between two elements allowing them to exchange finite amounts of energy and matter. Available strategies to each individual of one class in the population are the propensities or "willingness" to connect any individual of the other class. Following evolutionary game theory, we propose a mathematical model which explains the patterns of connections which emerge when individuals are able to find connection strategies that asymptotically optimize their fitness. The process explains the formation of a network for efficiently exchanging energy and matter among individuals and thus ensuring their survival in hostile environments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 2 5%
United States 1 2%
Unknown 41 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 34%
Researcher 9 20%
Student > Bachelor 4 9%
Professor > Associate Professor 3 7%
Student > Master 3 7%
Other 5 11%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 30%
Mathematics 3 7%
Medicine and Dentistry 3 7%
Computer Science 2 5%
Immunology and Microbiology 2 5%
Other 12 27%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 September 2014.
All research outputs
#13,175,336
of 23,577,654 outputs
Outputs from Frontiers in Microbiology
#9,121
of 26,073 outputs
Outputs of similar age
#106,044
of 237,132 outputs
Outputs of similar age from Frontiers in Microbiology
#74
of 163 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 26,073 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 63% 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 237,132 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 54% of its contemporaries.
We're also able to compare this research output to 163 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.