Analysis and Classification of Human Microbiomes: Detection of Bioindicators and Optimization through Machine Learning - Kasmanas, Jonas Coelho; Rocha, Ulisses Nunes da; Stadler, Peter F; Carvalho, André Carlos Ponce de Leon Ferreira de (Anais Estendidos do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS); 2026: Anais Estendidos do XXVI Simpósio Brasileiro de Computação Aplicada à Saúde, 2026)
The human microbiome plays a crucial role in health and disease, yet extracting meaningful insights from it remains challenging. This work presents an integrated framework: (1) the HumanMetagenomeDB, standardizing metadata from 69,000 human metagenomes; (2) MuDoGeR, a multi-domain genome recovery tool; (3) an evaluation of genome recovery biases; (4) gSpreadComp, a workflow for bacterial resistance-virulence; and (5) an AutoML-driven platform built on prokaryotic genomes enabling biologically interpretable feature selection. Together, these contributions enable researchers to move from raw metagenomic data to actionable biological insights at scale.