Yi‐An Tung

ezGeno automates deep neural network design for genomic data analysis, outperforming existing tools in efficiency and accuracy for tasks like TF binding prediction and enhancer activity prediction.

This study develops a deep learning model to predict enhancer activity in new cell types by integrating DNase data across multiple cell types.

GenEpi detects gene-based epistasis using machine learning, outperforming existing methods on simulated data and identifying disease-related variants in Alzheimer's disease.

SeqsLab annotates and interprets genetic variants from large personal genome cohorts using Spark for scalability and integrates with public databases for variant analysis.