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Metabolites 2012, 2(3), 429-457; doi:10.3390/metabo2030429

Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory

1 Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Kawazu 680-4, Iizuka, Fukuoka 820-8502, Japan 2 PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
Received: 24 May 2012 / Revised: 26 June 2012 / Accepted: 9 July 2012 / Published: 12 July 2012
(This article belongs to the Special Issue Metabolic Network Models)
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Formation and adaptation of metabolic networks has been a long-standing question in biology. With recent developments in biotechnology and bioinformatics, the understanding of metabolism is progressively becoming clearer from a network perspective. This review introduces the comprehensive metabolic world that has been revealed by a wide range of data analyses and theoretical studies; in particular, it illustrates the role of evolutionary events, such as gene duplication and horizontal gene transfer, and environmental factors, such as nutrient availability and growth conditions, in evolution of the metabolic network. Furthermore, the mathematical models for the formation and adaptation of metabolic networks have also been described, according to the current understanding from a perspective of metabolic networks. These recent findings are helpful in not only understanding the formation of metabolic networks and their adaptation, but also metabolic engineering.
Keywords: metabolic network; large-scale network analysis; evolution; environmental adaptation metabolic network; large-scale network analysis; evolution; environmental adaptation
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Takemoto, K. Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory. Metabolites 2012, 2, 429-457.

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