Contrary to the de-novo motif analysis, this approach let us directly assess differentiation motif occurrence and successfully identified known cofactors which were significant or marginally significant after multiple testing correction.
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Machine learning reveals STAT motifs as predictors for GR-mediated gene repression.
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