Navigating Data Challenges in Genomics and AI Implementation

Today’s guest is Dan Elton, a Staff Scientist at the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH). Dan returns to the program to explore how AI is advancing genetic research, from protein engineering to gene editing and risk prediction. One of the most significant breakthroughs in this space is AlphaFold, DeepMind’s AI model that predicts protein structures with unprecedented accuracy. While it does not analyze genetic sequences directly, its ability to model protein folding is transforming drug development and protein engineering. Dan also discusses the potential for AI to improve polygenic risk prediction, where machine learning models are being applied to assess disease risk based on genetic markers. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!