Ke Tang

Ke received her bachelor’s degree from the College of Life Sciences at Sichuan Normal University in 2020. She has developed two computational tools for single-cell omics analysis including SCRIP, which uses scATAC-seq to infer transcriptional regulator activity and reconstruct cell state–specific gene regulatory networks, and MetroSCREEN, which uses scRNA-seq to infer tumor microenvironment metabolic states and identify associated regulators. Her research focuses on three areas including (1) building a predictive framework for metabolic–epigenetic regulatory axes using single-cell multi-omics to link regulatory programs to cell fate, state transitions, and disease progression; (2) applying this framework to lung cancer immunotherapy datasets to study tumor microenvironment remodeling, immune state changes, and immunotherapy response and resistance; and (3) developing an agent-based system to automate and intelligently assist key steps in single-cell and spatial multi-omics analysis, including preprocessing, annotation, regulatory inference, interpretation, and visualization.