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New evidence on the robustness of metabolic networks
Date:9/4/2008

searchers were able to develop a quantitative measure of metabolic robustness: the more robust the network, the less the probability that small disturbances produce large cascades.

They found that the likelihood of large failure cascades in a metabolic network is unusually small, compared to what they would expect from comparable, randomly structured networks.

In other words, these metabolic networks have evolved to be exceptionally robust, adopting organizational structures that help minimize the potentially harmful impacts of gene deletions and mutations. Ottino and his colleagues developed a mathematical model describing the cascading failure phenomenon as a percolation-like process.

The cascading failure model opens up new possibilities for developing math- and statistics-based descriptions of how network structure affects metabolic function in biological systems. The relationship between metabolic structure and function is an important, lingering question for researchers in areas such as bioengineering and disease treatment in medicine, where one goal is to manipulate metabolic network structure in order to obtain desired behaviors.

The Northwestern team concludes it is possible that nature, in this case, is the best teacher: improved understanding of how cell metabolisms have evolved to handle failure cascades may provide clues as to how one might design synthetic networks for similar robustness.


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Contact: Megan Fellman
fellman@northwestern.edu
847-491-3115
Northwestern University
Source:Eurekalert

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