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Differential motif enrichment analysis (DMEA), and is a type of motif enrichment analysis. Motif enrichment analysis differs from de novo motif discovery in that a set of known, well-characterized motifs are part of the input to motif enrichment analysis. Motif enrichment analysis has two major strengths relative to motif discovery. Firstly, because the motifs come from curated motif databases, the identities of the biological molecules that bind them are known. Secondly, restricting attention to the curated set of motifs increases statistical power, allowing more subtle motif enrichments to be detected.