AI Powered Structural Biology and Genomics for Understanding and Treating Cancer

Catalog description

Using cancer as a throughline, this course explores the transformative impact of artificial intelligence (AI) and machine learning (ML) across modern biomedicine, from protein structure and its central role in therapeutic development to functional genomics and its importance in understanding cancer predication, development and progression and in developing treatments. Students will learn how AI is revolutionizing our understanding of proteins, gaining hands-on experience with deep learning prediction tools like AlphaFold. The course will explore the underlying biology of cancer development and progression. We will also discuss the methods used to collect different types of data and the complexity and variability of different data sets. The course will then connect these functional molecules to the “blueprints” of life, investigating how AI techniques are applied to foundational genomics research for tasks such as variant calling, gene expression analysis, and disease risk prediction. Finally, students will explore the integration of these structural and genomic insights throughout the modern drug discovery pipeline, from AI-driven target identification and virtual screening to generative models for novel drug design. This course bridges structural biology, genomics, and computational methods, preparing students for careers at the intersection of AI and biomedicine.