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
- Predicting Patients’ Response to Immunotherapy from Tumor Histopathology and Blood: Computational Science in Immuno-oncologyJuly 08, 2025Assessing the Tumor Microenvironment with Systems Immunology: Computational Science in Immuno-oncologyAugust 21, 2025Data Jamboree: Enhancing Childhood Cancer Data Sharing and UtilitySeptember 29, 2025 - September 30, 2025NCI Office of Data Sharing’s Annual Data Sharing Symposium 2025: How Data Advances the Impact of Cancer ResearchSeptember 30, 2025 - October 01, 2025Childhood Cancer Data Initiative (CCDI) Symposium 2025October 06, 2025 - October 07, 2025