Integrative analysis with microbial modelling and machine learning uncovers potential alleviators for ulcerative colitis.

ABSTRACT: Ulcerative colitis (UC) is a challenging form of inflammatory bowel disease, and its etiology is intricately linked to disturbances in the gut microbiome. To identify the potential alleviators of UC, we employed an integrative analysis combining microbial community modeling with advanced machine learning techniques. Using metagenomics data sourced from the Integrated Human Microbiome Project, we constructed individualized microbiome community models for each participant. Our analysis highlighted a significant decline in both α and β-diversity of strain-level microbial populations in UC subjects compared to controls. Distinct differences were also observed in the predicted fecal metabolite profiles and strain-to-metabolite contributions between the two groups. Using tree-based machine learn

SUBMITTER: Zhu J 

PROVIDER: S-EPMC10989691 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature