Study on network motifs in metabolic networks

Abstract

Local structure of complex network is one of most important characteristic to understand dynamic properties of complex networks. Recently, network motifs, subgraph patterns occurring in complex networks at numbers significantly higher than those in suitable randomized networks have received a lot of attention especially in biological systems. We found such motifs in metabolic networks of 43 organisms and using clustering method, we categorized 43 organisms based on subgraph pattern statistics and found tendency to find common substrates in cohesive subgraph patterns.