MNetDec: A Flexible Algorithm for Metabolic Network Decomposition

Relevant modules of a metabolic network can reveal the underlying structure of the metabolic system and hence provide the insight into its function. Modularity is a useful standard for decomposing a complex network. However, it has been shown that simply optimizing modularity failed to find the most natural community structure by overpartition or under partition the network. Here, a novel network decomposition algorithm, called MNetDec, is proposed by integrating the dendrogram and modularity features of a metabolic network. By dealing with MNetDec, the small modules with questionable biological function are eliminated. Moreover, the size of the smallest module and final number of the modules in the decomposition result can be flexibly set by the users based on their own specific needs. The application of this algorithm on brain specific human metabolic network shows that MNetDec can generate biological reasonable modules with high modularity.