| Project/Area Number |
16K17763
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Mathematical physics/Fundamental condensed matter physics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Sughiyama Yuki 東京大学, 生産技術研究所, 特任助教 (90756389)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 非平衡統計物理学 / 進化生物学 / 確率過程論 / 大偏差原理 / 機械学習 / 数理生物学 / 統計物理 / 熱力学 / 生物物理 |
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| Outline of Final Research Achievements |
In this work, by introducing the structure of steady-state thermodynamics cultivated in the nonequilibrium statistical physics into cell-growing systems, I revealed that the excess growth generated by environmental changes can be evaluated by Clausius inequality. To be more precise, it was found that the excess growth was bound by lineage fitness which can be observed in an experiment.
In the second half of the research, in order to explore the application to an experiment of E. coli, I devised a path integral approach for age-structured population dynamics. Moreover, by employing this approach, I constructed an algorithm for type inference on the lineage tree of E. coli.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は細胞増殖と言う生命科学的分野の問題に、非平衡統計物理学と言う数理物理の技法を用いて挑戦したものである。そのため、全ての研究結果は両分野の研究者が共に理解できるような形で論文にまとめている。従って、生命科学と物理学の間にある分野横断的な本研究は、双方の研究者が協力し新たなる学問領域を構築するための指針となる大きな発展性を持つ。また、研究後半で得られた細胞のタイプ推定アルゴリズムは、感染症ウィルスのタイプ変異の推定にも応用でき、疫学や人口学分野への貢献も期待できる。
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