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Establishing statistical inference theory for bio-systems and biological control theory using control engineering

Research Project

Project/Area Number 17K00398
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Life / Health / Medical informatics
Research InstitutionThe University of Tokyo

Principal Investigator

Kiryu Hisanori  東京大学, 大学院新領域創成科学研究科, 准教授 (80415778)

Project Period (FY) 2017-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords生命情報学 / カルマンフィルター / 微分方程式 / 機械学習 / 1細胞シーケンシング / バイオテクノロジー / バイオインフォマティクス / 確率微分方程式 / 一細胞RNAシーケンシング / 一細胞シーケンシング / 制御工学 / RNA-seq / イネ / トランスクリプトーム
Outline of Final Research Achievements

Due to the low cost of next generation sequencing experiments and the high performance of microscopes, there has been an increase in research on measuring changes in the state of life over time at the cellular level. In general, time-series data are expected to provide more accurate estimates of causal relationships among elements than data measured only at a single time point. However, at present, descriptive analysis methods such as clustering are mainly used to analyze these data, and there is not much research on estimating the mechanisms that cause life state changes from measurement data. Therefore, we have developed and implemented a new set of algorithms to apply the theory of Kalman filter, which is widely used in the field of control engineering, to biological data.

Academic Significance and Societal Importance of the Research Achievements

生命情報科学の分野では人工知能や機械学習といった最新のデータ科学技術を用いたデータ解析が数多く行われているが、これらの技術が既存の確立した物理・化学・生物学の知識と無矛盾な結果を出す保証はなく、自然現象とは関係ないデータの特徴を捉えているのではないかという懸念が常に残る。そこで我々は、制御工学の分野で用いられているカルマンフィルターの理論を活用して、微分方程式のパラメータを測定データから推定する手法を開発した。この手法を用いれば、既知の生命過程の知識を人工知能や機械学習のモデルと統合することが容易になるため、理論生物学の強力な道具立てになることが期待される。

Report

(5 results)
  • 2020 Annual Research Report   Final Research Report ( PDF )
  • 2019 Research-status Report
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (6 results)

All 2020 2019 2017 Other

All Journal Article (5 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 5 results,  Open Access: 3 results,  Acknowledgement Compliant: 1 results) Remarks (1 results)

  • [Journal Article] LincRNA alleviates cardiac systolic dysfunction under pressure overload.2020

    • Author(s)
      Kuwabara Y, Tsuji S, Nishiga M, Izuhara M, Ito S, Nagao K, Horie T, Watanabe S, Koyama S, Kiryu H, Nakashima Y, Baba O, Nakao T, Nishino T, Sowa N, Miyasaka Y, Hatani T, Ide Y, Nakazeki F, Kimura M, Yoshida Y, Inada T, Kimura T, Ono K.
    • Journal Title

      Commun Biol.

      Volume: 3 Issue: 1 Pages: 434-434

    • DOI

      10.1038/s42003-020-01164-0

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column2019

    • Author(s)
      Kiryu Hisanori、Ichikawa Yuto、Kojima Yasuhiro
    • Journal Title

      Algorithms for Molecular Biology

      Volume: 14 Issue: 1 Pages: 23-23

    • DOI

      10.1186/s13015-019-0158-3

    • Related Report
      2019 Research-status Report
    • Peer Reviewed
  • [Journal Article] Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations2019

    • Author(s)
      Kojima Yasuhiro、Matsumoto Hirotaka、Kiryu Hisanori
    • Journal Title

      Bioinformatics

      Volume: 36 Issue: 1 Pages: 221-231

    • DOI

      10.1093/bioinformatics/btz498

    • Related Report
      2019 Research-status Report
    • Peer Reviewed
  • [Journal Article] reactIDR: evaluation of the statistical reproducibility of high-throughput structural analyses towards a robust RNA structure prediction2019

    • Author(s)
      Kawaguchi Risa、Kiryu Hisanori、Iwakiri Junichi、Sese Jun
    • Journal Title

      BMC Bioinformatics

      Volume: 20 Issue: 3 Pages: 130-130

    • DOI

      10.1186/s12859-019-2645-4

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation2017

    • Author(s)
      Matsumoto, H., Kiryu, H., Furusawa, C., Ko, S.H., M., Ko, B.H., S., Gouda, N., Hayashi, T., Nikaido, I.
    • Journal Title

      Bioinformatics

      Volume: 印刷中 Issue: 15 Pages: 2314-2321

    • DOI

      10.1093/bioinformatics/btx194

    • Related Report
      2017 Research-status Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Remarks] SCODE Source

    • URL

      https://github.com/hmatsu1226/SCODE

    • Related Report
      2017 Research-status Report

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Published: 2017-04-28   Modified: 2022-01-27  

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