DNA-CRAFT combines class-conditioned discrete diffusion with conditional Monte Carlo tree guidance to generate regulatory DNA sequences that achieve higher predicted cell-type specificity and biological fidelity than prior diffusion, autoregressive, or optimization baselines.
We implemented a custom differentiable wrapper to compute MinGap scores fromDesign-Model’s output and backpropagate gradients directly to the input sequence representation
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Conditional Monte Carlo Tree Diffusion for Designing Cell-Type-Specific and Biologically Faithful Regulatory DNA
DNA-CRAFT combines class-conditioned discrete diffusion with conditional Monte Carlo tree guidance to generate regulatory DNA sequences that achieve higher predicted cell-type specificity and biological fidelity than prior diffusion, autoregressive, or optimization baselines.