Yuqi Tan, PhD
Postdoctoral Fellow
Stanford University
Dr. Tan is a computational biologist developing innovative tools to quantify cell identity, enhance stem cell engineering, and dissect cancer heterogeneity. During her Ph.D., she specialized in computational and quantitative analysis of single-cell RNA sequencing (scRNA-seq) data, contributing to multiple high-impact publications. As a postdoctoral researcher, she has advanced the integration of single-cell omics with multiplexed imaging to decode high-dimensional tissue architecture in cancer and psychiatric diseases. Her long-term vision is to leverage multi-omics and develop machine learning techniques for both 2D and 3D analysis to uncover how diverse cell types and their interactions shape development, aging, and disease.
On the way to a human 3D intestine atlas
Talk Title
Talk Description
Extending 2D multiplexed analysis pipelines to 3D is a logical step, but it also presents opportunities to enhance the framework by leveraging unique features of 3D data. This talk will highlight our efforts to adapt and streamline existing 2D pipelines for 3D imaging while exploring new approaches to capture the richness of 3D spatial information fully.