Research Overview

The tempo and mode of tumor evolution through space and time
We leverage multi-region, longitudinal, and/or single-cell genomic data combined with agent-based computational model to reveal the quantitative principles for the evolutionary dynamics of tumor growth and metastasis.
The tempo and mode of tumor evolution through space and time
The evolutionary patterns of cancer subpopulations under immune selection
We integrate multi-region sequencing, single cell transcriptomics and computational models to understand how cancer cells evolve to escape our immune surveillance and how immune selection drive the evolutionary trajectories of cancer cells.
The evolutionary patterns of cancer subpopulations under immune selection
The clonal dynamics of stem cells during tissue development and renewal
We combine lineage tracing, single-cell transcriptomics and mathematical models to study the clonal dynamics of stem cells during tissue development and renewal.
The clonal dynamics of stem cells during tissue development and renewal
Computational methods for single-cell lineage tracing data
We develop computational methods for analyzing single-cell lineage tracing and transcriptomic data, with an aim to understand the population dynamics of somatic cells during tissue development and tumor initiation.
Computational methods for single-cell lineage tracing data