Meeting Details
Date: 26-02-11
Time: 11:00-12:00
Location: Teams
Presenter: Dr. Daoud Meerzaman
Advancing Cancer Research Through AI-Driven, Integrative Proteogenomics and Predictive Modeling
Abstract: Advances in artificial intelligence (AI) and high-throughput molecular profiling are reshaping how we study and treat cancer. This presentation highlights how the Computational Genomics and Bioinformatics Branch (CGBB) is advancing cancer research through AI-driven, integrative proteogenomics and predictive modeling. By combining genomics, transcriptomics, proteomics, imaging, and clinical data, CGBB develops scalable, reproducible analytical pipelines and machine learning frameworks to characterize tumor heterogeneity, identify predictive biomarkers, and model treatment response and patient outcomes. Emphasis is placed on enterprise-ready AI tools, high-performance computing, and collaborative, cross-branch efforts that enable robust validation, data sharing, and translational impact. Together, these approaches support NCI’s mission to accelerate data-driven discovery and advance precision oncology across diverse cancer types.