Title |
Environmental versatility promotes modularity in genome-scale metabolic networks
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Published in |
BMC Systems Biology, August 2011
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DOI | 10.1186/1752-0509-5-135 |
Pubmed ID | |
Authors |
Areejit Samal, Andreas Wagner, Olivier C Martin |
Abstract |
The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Japan | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 5% |
Germany | 2 | 2% |
Iran, Islamic Republic of | 2 | 2% |
Norway | 1 | 1% |
Hungary | 1 | 1% |
Switzerland | 1 | 1% |
Canada | 1 | 1% |
Unknown | 87 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 27 | 27% |
Student > Ph. D. Student | 26 | 26% |
Student > Master | 10 | 10% |
Professor > Associate Professor | 8 | 8% |
Student > Bachelor | 6 | 6% |
Other | 14 | 14% |
Unknown | 9 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 48 | 48% |
Biochemistry, Genetics and Molecular Biology | 12 | 12% |
Computer Science | 8 | 8% |
Engineering | 5 | 5% |
Physics and Astronomy | 3 | 3% |
Other | 11 | 11% |
Unknown | 13 | 13% |