Zhenhao Zhang

This paper introduces a supervised foundation model for plant regulatory genomics that predicts chromatin state from genomic sequence, showing improved speed, accuracy, and interpretability over DNA language models.

EPCOT is a deep learning framework that predicts epigenome, chromatin organization, transcriptome, and enhancer activity, showing generalizability across cell types and modalities.

The paper introduces ECHO, a graph-based deep learning model that predicts chromatin features using 3D chromatin organization, showing improved performance over sequence-based models.