Bayesian Learning for Microbioma

In this project, we utilize Bayesian Dirichlet models to analyze the impact of stress on vaginal microbiome composition. By examining cortisol levels in hair and blood as proxies for stress, the study explores how mental health disturbances influence microbial communities. The research involves genetic analysis of microbiota from 259 middle-aged women, identifying key bacterial profiles linked to vaginal health. Findings suggest that variations in Lactobacillus spp. and other genera may indicate dysbiosis related to stress. This project aims to enhance understanding of the microbiome's role in health and disease, guiding future therapeutic strategies.