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Emergence and maintenance of functional modules in signaling pathways

Overview of attention for article published in BMC Ecology and Evolution, October 2007
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Title
Emergence and maintenance of functional modules in signaling pathways
Published in
BMC Ecology and Evolution, October 2007
DOI 10.1186/1471-2148-7-205
Pubmed ID
Authors

Orkun S Soyer

Abstract

While detection and analysis of functional modules in biological systems have received great attention in recent years, we still lack a complete understanding of how such modules emerge. One theory is that systems must encounter a varying selection (i.e. environment) in order for modularity to emerge. Here, we provide an alternative and simpler explanation using a realistic model of biological signaling pathways and simulating their evolution. These evolutionary simulations start with a homogenous population of a minimal pathway containing two effectors coupled to two signals via a single receptor. This population is allowed to evolve under a constant selection pressure for mediating two separate responses. Results of these evolutionary simulations show that under such a selective pressure, mutational processes easily lead to the emergence of pathways with two separate sub-pathways (i.e. modules) each mediating a distinct response only to one of the signals. Such functional modules are maintained as long as mutations leading to new interactions among existing proteins in the pathway are rare. While supporting a neutralistic view for the emergence of modularity in biological systems, these findings highlight the relevant rate of different mutational processes and the distribution of functional pathways in the topology space as key factors for its maintenance.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 5%
France 1 2%
Switzerland 1 2%
United Kingdom 1 2%
Brazil 1 2%
Unknown 36 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 33%
Researcher 11 26%
Professor 3 7%
Student > Master 3 7%
Student > Bachelor 2 5%
Other 6 14%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 57%
Biochemistry, Genetics and Molecular Biology 7 17%
Computer Science 3 7%
Mathematics 1 2%
Physics and Astronomy 1 2%
Other 2 5%
Unknown 4 10%