Deep neural networks identify sequence context features predictive of transcription factor binding.

Nat Mach Intell · 2021 · PMC8009085 · PMID 33796819

Europe PMC DOI

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highly significantP =1.2×10 −245actually significant

However, in the DNaseI-controlled model, the GATA motif is highly significant (one-sided P =1.2×10 −245 , OR=11.5) for NRSF, suggesting a potential role for this sequence in promoting nearby NRSF binding after the surrounding region is made accessible by pioneer factors.

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