How network makes metabolomics signals sharper

Dr. Ali Salehzadeh-Yazdi
Constructor University Bremen
Bremen | Germany
Part of the Symposium:
Metabolomics India 2023 - Clinical applications
In the domain of systems medicine and biotechnology, elucidating the genotype-phenotype interplay relies on a genome-scale metabolic framework. Genome-scale Metabolic models (GEMs) serve as foundational tools, enabling comprehensive analyses of genetic perturbations, metabolic engineering, and disease mechanisms. Integrating omics data into GEMs enhances predictive accuracy, while innovative approaches like the translation of transcription data into biologically relevant gene sets further refine metabolic predictions. This study leverages context-specific GEMs to illuminate the intricate connections between genotype and phenotype in diverse applications. Machine learning-driven classification based on unique metabolic fingerprints reveals distinct features across applications, shedding light on the nuanced landscape of systems medicine and biotechnology. These insights bridge genetic and phenotypic realms, paving the way for precision interventions and transformative advancements.
Dr. Salehzadeh-Yazdi @LinkedIn: / ali-salehzadeh-yazdi-9...
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