2012 IEEE International Conference on Granular Computing
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Abstract

The biological data flood makes more and more genome-scale biological networks available. There is a need to identify functional modules in these biological networks, complex networks based methods offer promise in this regard. Here, we show that EAGLE algorithm can be used for functional modules identification. By applying the algorithm to the giant strong component (GSC) of Staphylococcus aureus metabolic network, we obtain 12 functional modules. We find that all of 12 identified functional modules have high modularity, and they also have obvious biological insights, which suggested the high efficiency of using EAGLE algorithm to identify functional modules in biological networks.
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