MInfer: Bridging MetaboAnalyst and Jacobian analysis for metabolomic networks
Jazyk angličtina Země Irsko Médium print-electronic
Typ dokumentu časopisecké články
PubMed
39999596
DOI
10.1016/j.cmpb.2025.108672
PII: S0169-2607(25)00089-6
Knihovny.cz E-zdroje
- Klíčová slova
- Dynamic relationships, Metabolite interactions, Metabolomic data analysis, Systems biology,
- MeSH
- algoritmy MeSH
- lidé MeSH
- metabolické sítě a dráhy * MeSH
- metabolomika * MeSH
- software MeSH
- výpočetní biologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND AND OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Department of Medical Biochemistry Oslo University Hospital Oslo Norway
Faculty of Biology Plant Evolutionary Cell Biology Ludwig Maximilians Universität München Germany
Molecular Systems Biology University of Vienna Vienna Austria
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