network link prediction by global silencing of indirect correlations
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TLDR
The fundamental properties of dynamical correlations in networks are exploited to develop a method to silence indirect effects and help translate the abundant correlation data into valuable local information, with applications ranging from link prediction to inferring the dynamical mechanisms governing biological networks.Abstract:
By mathematically 'silencing' spurious, indirect correlations in networks, two groups devise approaches for improving many different types of network analyses.read more
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References
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