2021 Fiscal Year Final Research Report
Functional classification of long noncoding RNAs based on functional elements and deep learning
| Project/Area Number |
16H05879
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
Life / Health / Medical informatics
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| Research Institution | Waseda University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Keywords | lncRNA / ノンコーディングRNA |
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| Outline of Final Research Achievements |
To elucidate the function of long non-coding RNAs (lncRNAs), which are not translated into proteins but have their own functions, we have conducted many studies from an informatics perspective, focusing on "functional elements" such as RNA sequences, structures, modifications, and interactions with biological macromolecules. For example, we attempted to elucidate the functions of lncRNAs by clarifying that repeat sequences, which were thought to be junk, contribute to the tissue-specific expression of lncRNAs and to their interactions with proteins and DNA. Through these efforts, we have established information infrastructure technology that contributes to the classification of lncRNA functions, and have made it widely available to the public.
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| Free Research Field |
バイオインフォマティクス
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| Academic Significance and Societal Importance of the Research Achievements |
現在機能のわかっていないlncRNAの中には，がんや神経変性疾患などの重篤な疾患と関連するものが存在すると考えられている．今回開発した技術や解析結果により，今後lncRNAと疾患との関連性が明らかになった暁には，RNAをターゲットにした医学・薬学研究などに発展する可能性が高い．
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