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Development of cell differentiation in the transition to multicellularity: a dynamical modeling approach

Overview of attention for article published in Frontiers in Microbiology, June 2015
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  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
Development of cell differentiation in the transition to multicellularity: a dynamical modeling approach
Published in
Frontiers in Microbiology, June 2015
DOI 10.3389/fmicb.2015.00603
Pubmed ID
Authors

Emilio Mora Van Cauwelaert, Juan A. Arias Del Angel, Mariana Benítez, Eugenio M. Azpeitia

Abstract

Multicellularity has emerged and continues to emerge in a variety of lineages and under diverse environmental conditions. In order to attain individuality and integration, multicellular organisms must exhibit spatial cell differentiation, which in turn allows cell aggregates to robustly generate traits and behaviors at the multicellular level. Nevertheless, the mechanisms that may lead to the development of cellular differentiation and patterning in emerging multicellular organisms remain unclear. We briefly review two conceptual frameworks that have addressed this issue: the cooperation-defection framework and the dynamical patterning modules (DPMs) framework. Then, situating ourselves in the DPM formalism first put forward by S. A. Newman and collaborators, we state a hypothesis for cell differentiation and arrangement in cellular masses of emerging multicellular organisms. Our hypothesis is based on the role of the generic cell-to-cell communication and adhesion patterning mechanisms, which are two fundamental mechanisms for the evolution of multicellularity, and whose molecules seem to be well-conserved in extant multicellular organisms and their unicellular relatives. We review some fundamental ideas underlying this hypothesis and contrast them with empirical and theoretical evidence currently available. Next, we use a mathematical model to illustrate how the mechanisms and assumptions considered in the hypothesis we postulate may render stereotypical arrangements of differentiated cells in an emerging cellular aggregate and may contribute to the variation and recreation of multicellular phenotypes. Finally, we discuss the potential implications of our approach and compare them to those entailed by the cooperation-defection framework in the study of cell differentiation in the transition to multicellularity.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
France 1 2%
Unknown 56 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Student > Bachelor 8 14%
Researcher 8 14%
Student > Master 6 10%
Student > Doctoral Student 4 7%
Other 12 21%
Unknown 9 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 47%
Biochemistry, Genetics and Molecular Biology 15 26%
Environmental Science 2 3%
Computer Science 2 3%
Nursing and Health Professions 1 2%
Other 3 5%
Unknown 8 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 10 July 2016.
All research outputs
#6,042,566
of 22,808,725 outputs
Outputs from Frontiers in Microbiology
#5,783
of 24,760 outputs
Outputs of similar age
#69,578
of 263,999 outputs
Outputs of similar age from Frontiers in Microbiology
#81
of 382 outputs
Altmetric has tracked 22,808,725 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 24,760 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. 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 263,999 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 73% of its contemporaries.
We're also able to compare this research output to 382 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.