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Does Habitat Variability Really Promote Metabolic Network Modularity?

Overview of attention for article published in PLOS ONE, April 2013
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Title
Does Habitat Variability Really Promote Metabolic Network Modularity?
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0061348
Pubmed ID
Authors

Kazuhiro Takemoto

Abstract

The hypothesis that variability in natural habitats promotes modular organization is widely accepted for cellular networks. However, results of some data analyses and theoretical studies have begun to cast doubt on the impact of habitat variability on modularity in metabolic networks. Therefore, we re-evaluated this hypothesis using statistical data analysis and current metabolic information. We were unable to conclude that an increase in modularity was the result of habitat variability. Although horizontal gene transfer was also considered because it may contribute for survival in a variety of environments, closely related to habitat variability, and is known to be positively correlated with network modularity, such a positive correlation was not concluded in the latest version of metabolic networks. Furthermore, we demonstrated that the previously observed increase in network modularity due to habitat variability and horizontal gene transfer was probably due to a lack of available data on metabolic reactions. Instead, we determined that modularity in metabolic networks is dependent on species growth conditions. These results may not entirely discount the impact of habitat variability and horizontal gene transfer. Rather, they highlight the need for a more suitable definition of habitat variability and a more careful examination of relationships of the network modularity with horizontal gene transfer, habitats, and environments.

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Geographical breakdown

Country Count As %
United States 2 5%
Japan 2 5%
Germany 1 3%
United Kingdom 1 3%
Mexico 1 3%
Portugal 1 3%
Singapore 1 3%
Belgium 1 3%
Unknown 30 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 40%
Student > Ph. D. Student 11 28%
Student > Master 5 13%
Other 2 5%
Professor 2 5%
Other 2 5%
Unknown 2 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 50%
Biochemistry, Genetics and Molecular Biology 4 10%
Environmental Science 3 8%
Computer Science 2 5%
Social Sciences 2 5%
Other 4 10%
Unknown 5 13%