Mapping Tumor Heterogeneity Across Space and Time
Princeton University’s Dr. Ben Raphael will explain the computational methods his team has developed to help you analyze tumor heterogeneity using genomics and spatial transcriptomics technologies. He’ll also share machine learning methods to study tumor evolution in 2D and 3D space. You will see these open-source tools in action as he demonstrates how to use them to analyze data from different cancer types and molecular profiling technologies.
The NCI Emerging Technologies Seminar Series highlights novel technologies supported through NCI awards that could transform cancer research and clinical care.
Dr. Raphael runs the Raphael Lab at Princeton University. His research focuses on bioinformatics and computational biology and his interests include cancer genomics and evolution, single-cell and spatial sequencing, network analysis of disease mutations, genome rearrangements, and structural variation.
Upcoming Events
- AI-Driven Spatial Transcriptomics Unlocks Large-Scale Breast Cancer Biomarker Discovery from HistopathologyMay 07, 2025Co-clinical Imaging Research Resource Program (CIRP) Annual Virtual Meeting 2025—Celebrating A Ten-Year MilestoneMay 07, 2025 - May 08, 2025Workshop Series: Synthetic and Systems Approaches to Interrogate Spatiotemporal Processes in CancerMay 13, 2025 - May 20, 2025Pediatric Preclinical In Vivo Testing (PIVOT) Program: Advancing Targeted Therapies for Childhood CancersMay 13, 2025Agentic AI in Cancer ResearchMay 27, 2025