| Budget Amount *help |
¥17,030,000 (Direct Cost: ¥13,100,000、Indirect Cost: ¥3,930,000)
Fiscal Year 2020: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2019: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2018: ¥8,190,000 (Direct Cost: ¥6,300,000、Indirect Cost: ¥1,890,000)
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| Outline of Final Research Achievements |
We developed a theoretical framework for analyzing and designing the dynamics of biomolecular systems using a mathematical model, and an experimental platform that efficiently supplements data necessary for constructing such models. Specifically, we developed a modeling framework that combines the first-principles model derived from physical laws with a machine learning model learned from experimental data. The proposed framework enabled robust prediction and analysis of systems' dynamics that takes into account the influence of environmental factors, which was difficult to capture with the first-principles model alone. A microfluidic system was also developed to generate a large number of parallel reaction systems with slightly different environmental factors and use for model identification.
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