Work

MInfer: Bridging MetaboAnalyst and Jacobian analysis for metabolomic networks

Year: 2025

Type: article

Abstract: • Novel computational tool: MInfer integrates MetaboAnalyst and Jacobian analysis for dynamic metabolomic network inference. • Enhanced data interpretation: captures both metabolic pathways and metabolite interactions for deeper insights. • User-friendly R packages: provides a seamless transition from MetaboAnalyst workflows to advanced network analysis. • Biological insights: reveals critical metabolic pathways and interactions in disease and metabolism. • Innovation in metabolomics: enables predictive modeling of metabolic changes with interdisciplinary potential. Metabolomic interaction networks provide critical insights into the dynamic relationships between metabolites and their regulatory mechanisms. This study introduces MInfer, a novel computational framework that integrates outputs from MetaboAnalyst, a widely used metabolomic analysis tool, with Jacobian analysis to enhance the derivation and interpretation of these networks. MInfer combines the comprehensive data processing capabilities of MetaboAnalyst with the mathematical modeling power of Jacobian analysis. This framework was applied to various metabolomic datasets, employing advanced statistical tests to construct interaction networks and identify key metabolic pathways. The application of MInfer revealed significant metabolic pathways and potential regulatory mechanisms across multiple datasets. The framework demonstrated high precision, sensitivity, and specificity in identifying interactions, enabling robust network interpretations. MInfer enhances the interpretation of metabolomic data by providing detailed interaction networks and uncovering key regulatory insights. This tool holds significant potential for advancing the study of complex biological systems.

Source: Computer Methods and Programs in Biomedicine

DOI: 10.1016/j.cmpb.2025.108672