Microbiome-based phenotypic prediction with AI

Music City Center 

The human microbiome offers valuable insights into health and disease, yet leveraging it for accurate phenotypic prediction remains challenging. In this talk, I will present two AI-driven approaches that integrate biological knowledge to enhance microbiome-based prediction. One harnesses microbial phylogeny to improve clinical outcome prediction, while the other employs large language models guided by domain knowledge to enable more accurate and efficient disease diagnosis. Together, these strategies demonstrate the potential of combining AI with biological insight to improve phenotypic prediction from microbiome profiles.

AlphaFold2

Computational Pipeline

Function-Based Annotations

Human Virome Catalog

Protein 3D Structures