Zhihan Zhou

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.

DNABERT is a pre-trained transformer model for DNA sequences that achieves state-of-the-art performance on sequence prediction tasks and enables visualization of nucleotide-level importance across species.