Overview

• VBayesMM, a variational Bayesian neural network, uncovers gut microbe–metabolite relationships that traditional analytical tools cannot reliably detect.
• Applied to sleep disorder, obesity and cancer datasets, the model consistently outperformed standard methods and pinpointed bacterial families tied to known biological processes.
• The framework quantifies uncertainty in its predictions to prevent overconfidence and help researchers assess the reliability of identified interactions.
• Researchers are tackling data sparsity, microbial interdependencies and high computational demands to improve accuracy and analysis speed.
• Future developments include integrating comprehensive chemical datasets and microbial phylogenies to advance targeted microbial therapies and dietary interventions.