Metabolic networks are composed of several functional modules, reproducing metabolic pathways and describing the entire cellular metabolism of an organism. In the last decade, an enormous interest has grown for the study of tolerance to errors and attacks in metabolic networks. Studies on their robustness have suggested that metabolic networks are tolerant to errors, but very vulnerable to targeted attacks against highly connected nodes. However, many findings on metabolic networks suggest that the above classification is too simple and imprecise, since hub node attacks can be bypassed if alternative metabolic paths can be exploited. On the contrary, non-hub nodes attacks can affect cell survival when the node is the only path within a functional module. In this paper an integrated approach for metabolic networks robustness analysis is presented. With more details, statistical, topological, and functional analysis are used together to evaluate metabolic network behavior under normal operation conditions and under random or targeted attacks. Two real biological metabolic networks have been used to test the effectiveness of the proposed approach.
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