Wen Group

Cell-Type-Resolved Chromatin Effects of AD/PD Variants: DNA Language Model vs. ChromBPNet. We asked whether a general DNA language model can rival the specialized CNN ChromBPNet at predicting how non-coding variants affect chromatin accessibility. We fine-tuned our model, NucEL, on the same brain DNase-seq and GM12878 ATAC data and ran ChromBPNet's own endpoints. NucEL beat zero-shot ChromBPNet at accessibility classification in all four brain cell types and on GM12878 (0.967 vs 0.899), and independently reproduced ChromBPNet's variant-effect atlas (ρ=0.50; CR1 the shared top AD hit). A 1×→50× scaling curve shows the gap is data-limited, not architectural — suggesting general sequence models can match purpose-built regulatory CNNs given enough data.