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Network alignment is a fundamental problem in several domains that aims at mapping nodes across networks. Here, the authors develop a probabilistic approach that assumes that observed networks are errorful copies from a blueprint. The method samples the distribution of alignments, improving accuracy and enabling potential applications.

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