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rich molecular cargo, which is characterised using multi-omics approaches to identify biomarkers at the transcriptomic, proteomic, and lipidomic levels. The project comprises several steps, including
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their struggles are hindered. GENMAR’s research objective is situated at the intersection of these three knowledge gaps. The project will develop a multi-sited, multi-scalar, comparative and theorized ethnography
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computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
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