Discovered a cluster associated with novel cancer-related gene mutations in liver cancer cells from 300 patients; found another new cluster in subsequent colorectal cancer analysis. Also, revealed that for cancers in immune-privileged sites (e.g., uveal melanoma and low-grade gliomas), higher immune activity correlates with worse overall survival, elucidating the mechanism behind this phenomenon.
Research Experience
Focused on analyzing the molecular-level dynamics of diseases like cancer using a large amount of biomolecular data (such as spatio-temporal omics, imaging data, and clinical information) combined with mathematical/computational techniques such as deep learning. The goal is to discover new causes of disease and reconstruct quantitative networks among these factors to understand disease mechanisms as a whole system.
Background
Research interests include genomic medicine, precision medicine, tumor microenvironment, deep learning, mathematical simulation, and quantum computing. Aiming to understand life phenomena and diseases through advanced mathematical science and molecular observation technology.
Miscellany
Developed a unique technique called 'DeepInsight' that transforms omics data into an image-like format and applies convolutional neural networks to it, enabling the distinction between different types of cancer.