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Community detection partitions a network into groups according to a specified structural criterion, often excess internal connectivity. The output depends on the objective, so a partition inferred from topology need not by itself establish distinct biological functions.

The Louvain method is a greedy multilevel community detection algorithm maximizing network modularity. It alternates positive-gain single-vertex moves with contraction of communities into weighted vertices. Different vertex orders can produce different local optima; a result is not a certificate of globally maximum modularity.^[ref]