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Analysis and prediction of nutritional requirements using structural properties of metabolic networks and support
Takeyuki Tamura1, Nils Christian, Kazuhiro Takemoto
1Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan. tamura@kuicr.kyoto-u.ac.jp
Abstract:
Properties of graph representation of genome scale metabolic networks have been extensively studied. However, the relationship between these structural properties and functional properties of the networks are still very unclear. In this paper, we focus on nutritional requirements of organisms as a functional property and study the relationship with structural properties of a graph representation of metabolic networks. In order to examine the relationship, we study to what extent the nutritional requirements can be predicted by using support vector machines from structural properties, which include degree exponent, edge density, clustering coefficient, degree centrality, closeness centrality, betweenness centrality and eigenvector centrality. Furthermore, we study which properties are influential to the nutritional requirements.
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