Christopher Yin

The paper designs cell type-specific enhancers using deep learning models trained on chromatin accessibility data and validates their function across human and mouse cell types.

This study uses iterative deep learning to design human enhancers with cell type-specific activity, validated through experimental testing and perturbation experiments.

This study creates a single-cell multi-omics atlas of zebrafish embryogenesis and identifies transcription factors that drive cell-type-specific chromatin landscapes and instant differentiation.