| Project/Area Number |
17K15132
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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 |
Developmental biology
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| Research Institution | Institute of Physical and Chemical Research |
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Principal Investigator |
Onimaru Koh 国立研究開発法人理化学研究所, 生命機能科学研究センター, 基礎科学特別研究員 (30787065)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
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| Keywords | 深層学習 / 形態形成 / 転写制御配列 / ディープラーニング / ゲノム解析 / 転写制御 / 機械学習 / 遺伝子制御 / 次世代シーケンサー / ゲノム配列比較解析 / 進化発生学 |
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| Outline of Final Research Achievements |
This project was aimed at development of transcriptional regulatory prediction methods in morphogenesis by applying deep learning. We set the following two tasks to achieve this goal: a) the genome-wide identification of morphogenic transcriptional enhancers using mouse limb buds; b) developing deep learning methods to analyze enhancer sequences and infer gene regulatory networks. We successfully determined limb-associated morphogenic enhancers and analyzed the characteristics of these sequences. Moreover, we developed a deep learning-based regulatory sequence classifier that outperformed previous studies. This software can extract information that is critical for transcriptional regulation from genomic sequences. As an output of this project, we have published one peer-reviewed original research paper and two original research papers as preprints and released the developed program as an open-source software.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究成果における学術的な意義は、形態形成における転写制御配列について新たな特徴、傾向を発見し、転写制御と形態の多様性について理解を深めることに貢献したことにある。また、深層学習を用いた新たなゲノム配列の解析方法の提案が出来、ゲノム配列と生物の形態を結びつける研究が発展する上で礎となることが期待される。社会貢献としては、本研究は、ヒトの個々のゲノム配列に対する新たな解釈を行う上で、基礎的な知見が得られ、技術開発のさきがけとなる成果が得られたと考えている。
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