Advancing Microbiome Data for AI Applications
Speaker:
Rob Knight, PhD, Wolfe Family Endowed Chair in Microbiome Research at Rady Children's; Director, Center for Microbiome Innovation; Professor, Department of Pediatrics, Department of Computer Science & Engineering, Shu Chien-Gene Lay Department of Bioengineering, and Halicioglu Data Science Institute, University of California San Diego
Contact Hours:
1.0
Date:
July 22, 2025 - July 31, 2026
Description:
Microbiome research has rapidly expanded across multiple areas of human health. There is growing interest in developing large, AI-ready datasets to explore modifiable microbial factors. Achieving this requires standardized collection of data and metadata at scale. This webinar explores the evolution of the field - from ecological methods and machine learning to the current AI revolution - highlighting the use of large citizen-science datasets. It also addresses key challenges in producing high-throughput microbiome and metabolome data. Finally, it considers how discoveries in adult populations may translate to pediatric care as certain diseases emerge earlier in life.
Learning Objectives:
- Describe strengths and weaknesses of ecological, machine learning, and AI approaches to analyzing microbiome data.
- Provide an overview of how AI microbiome analysis works.
- Discuss the ethical issues that need to be overcome to produce unbiased AI-ready microbiome datasets.