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Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition

Overview of attention for article published in PLoS Computational Biology, November 2008
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Title
Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition
Published in
PLoS Computational Biology, November 2008
DOI 10.1371/journal.pcbi.1000226
Pubmed ID
Authors

Andreea Munteanu, Ricard V. Solé

Abstract

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 6%
United States 4 5%
Germany 2 2%
Italy 2 2%
New Zealand 2 2%
Turkey 1 1%
Austria 1 1%
Brazil 1 1%
Israel 1 1%
Other 5 6%
Unknown 57 70%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 32%
Researcher 20 25%
Professor 9 11%
Student > Master 7 9%
Professor > Associate Professor 5 6%
Other 11 14%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 53%
Biochemistry, Genetics and Molecular Biology 10 12%
Computer Science 7 9%
Business, Management and Accounting 2 2%
Economics, Econometrics and Finance 2 2%
Other 12 15%
Unknown 5 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 September 2011.
All research outputs
#20,817,194
of 25,576,801 outputs
Outputs from PLoS Computational Biology
#8,249
of 9,003 outputs
Outputs of similar age
#170,273
of 181,948 outputs
Outputs of similar age from PLoS Computational Biology
#39
of 42 outputs
Altmetric has tracked 25,576,801 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.