Research Areas

What We Investigate

Total Omics Data Analysis — from the single-cell level to population-scale, powered by AI and advanced statistical methodology.

DNA Sequencing
01 / Genomics

DNA Sequencing

We conduct research on diverse NGS-based DNA sequencing approaches to understand the genetic changes underlying disease and biological aging. Our lab currently focuses on bone aging, cancer genomics, and diverse mouse and human disease models.

WGS WXS Target Panel GWAS
RNA Sequencing
02 / Transcriptomics

RNA Sequencing

From bulk RNA-seq to cutting-edge single-cell and spatial transcriptomics, we extract temporal signals, cellular communication networks, and gene expression dynamics. We apply machine learning and statistical frameworks to reveal biological insights — including Aging and Alzheimer's disease studied through the latest spatial platforms.

scRNA-seq Bulk RNA-seq Spatial Transcriptomics Multiome
Epigenome
03 / Epigenomics

Epigenome Sequencing

We study the regulatory landscape of the genome through diverse epigenetic modalities — decoding how chromatin accessibility, histone modifications, and 3D genome architecture shape gene expression during cellular differentiation and disease. We are actively expanding to single-cell epigenomics.

ATAC-seq ChIP-seq Hi-C scATAC-seq
AI and Machine Learning
04 / AI & Methodology

Data Analysis & AI

We integrate diverse statistical approaches and bioinformatics pipelines with GPU-accelerated deep learning for multi-omics analysis. From classical machine learning to cutting-edge AI, we develop novel methodologies and analytical tools to interpret complex genomic data and build next-generation clinical prediction models.

Deep Learning Machine Learning Biomarker Discovery GPU Computing