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Tue. Nov 26, 2024

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Rapid adaptation to environmental changes in evolution experiments and its predictive control

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Until now, research aimed at solving real-world problems in life sciences involved analyzing experimental and clinical data obtained in the real world using statistical approaches. However, in the era of artificial intelligence, including machine learning and deep learning, the landscape of life science research is changing. For instance, by analyzing real-world data with mathematical models, it becomes possible to develop quantitative computer simulations, enabling comprehensive analysis in the virtual world. The insights gained can then be applied in the real world. In this symposium, we will discuss the approach to life science research using cutting-edge AI technology, providing concrete examples and exploring future perspectives.<br>

The 47th Annual Meeting of the Molecular Biology Society of Japan

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[2MS-14-04]Rapid adaptation to environmental changes in evolution experiments and its predictive control

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