Quantitative Biology > Populations and Evolution
[Submitted on 26 Jun 2008 (v1), last revised 3 Jul 2008 (this version, v2)]
Title:Communities recognition in the Chesapeake Bay ecosystem by dynamical clustering algorithms based on different oscillators systems
View PDFAbstract: We have recently introduced an efficient method for the detection and identification of modules in complex networks, based on the de-synchronization properties (dynamical clustering) of phase oscillators. In this paper we apply the dynamical clustering tecnique to the identification of communities of marine organisms living in the Chesapeake Bay food web. We show that our algorithm is able to perform a very reliable classification of the real communities existing in this ecosystem by using different kinds of dynamical oscillators. We compare also our results with those of other methods for the detection of community structures in complex networks.
Submission history
From: Alessandro Pluchino [view email][v1] Thu, 26 Jun 2008 10:17:13 UTC (1,449 KB)
[v2] Thu, 3 Jul 2008 17:01:05 UTC (1,449 KB)
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