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Mon. Jul 7, 2025

Tue. Jul 8, 2025

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Machine Learning for Efficient and Robust Simulations of Reactive-Transport Systems Integrated with Microbial Metabolic Networks

Microbial metabolism is a complex system composed of an extensive array of biochemical reactions. In ecosystems, microbial species with diverse metabolic pathways exchange metabolic products, expanding the metabolic network across entire communities into more complex forms. This community-level metabolic network forms the foundational framework that shapes biogeochemical cycles and energy flows within ecosystems. Understanding the detailed metabolic interactions of environmental microorganisms, along with the processes of their growth and environmental modification, is crucial for deciphering the co-development of organisms and their environment, and for predicting environmental changes. To achieve this, it is necessary to reconstruct traditional microbial modeling from the perspective of metabolic systems, enabling the advancement of mathematical models integrated with environmental omics data. This session brings together leading researchers at the forefront of cutting-edge efforts, fostering discussions aimed at advancing our understanding of microbial community interactions within metabolic contexts.

Unraveling microbial community dynamics through metabolic interactions

Joint Meeting of Asian Conference for Mathematical Biology and Annual Meeting of Japanese Society for Mathematical Biology (ACMB-JSMB2025)

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[SS23-03]Machine Learning for Efficient and Robust Simulations of Reactive-Transport Systems Integrated with Microbial Metabolic Networks

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