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BMC Bioinformatics 2007
Correlation between structure and temperature in prokaryotic metabolic networksAbstract: For this, we investigate the correlations between several structural properties characterized by graph metrics like the edge density, the degree exponent, the clustering coefficient, and the subgraph concentration in the metabolic networks of 113 prokaryotes and optimal growth temperature. As a result, we find that these structural properties are correlated with the optimal growth temperature. With increasing temperature, the edge density, the clustering coefficient and the subgraph concentration decrease and the degree exponent becomes large.This result implies that the metabolic networks transit with temperature as follows. The density of chemical reactions becomes low, the connectivity of the networks becomes homogeneous such as random networks and both the network modularity, based on the graph-theoretic clustering coefficient, and the frequency of recurring subgraphs decay. In short, metabolic networks undergo a change from heterogeneous and high-modular structures to homogeneous and low-modular structures, such as random networks, with temperature. This finding may suggest that the temperature plays an important role in the design principles of metabolic networks.Elucidation of basic design principles of biological networks is important to understand the cell's internal organization and its adaptation to environmental changes [1]. A large amount of data on molecular interaction networks has recently been accumulated using several new technologies and high-throughput methods. In particular, the increasing number of data on many different organisms has made it possible to trace back the evolutionary history of metabolic networks, and uncover the major structural similarities and differences among species.The ordinary classification of organisms includes three domains of life [2] (Archaea, Bacteria and Eukaryote) and it is based on cellular organization and similarities among organisms, reflecting common evolutionary history of the species. Archaea and bacteria h
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