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単粒子解析におけるタンパク質構造分類のための深層学習アプローチの動向
http://hdl.handle.net/10228/00008707
http://hdl.handle.net/10228/00008707ee994132-a0f4-4ebd-96da-fef89d6e4f5c
名前 / ファイル | ライセンス | アクション |
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kenbikyo.55.3_104.pdf (2.0 MB)
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Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||
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公開日 | 2022-02-02 | |||||||||||
資源タイプ | ||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
資源タイプ | journal article | |||||||||||
タイトル | ||||||||||||
言語 | ja | |||||||||||
タイトル | 単粒子解析におけるタンパク質構造分類のための深層学習アプローチの動向 | |||||||||||
タイトル | ||||||||||||
言語 | en | |||||||||||
タイトル | Trends in Deep Learning Approaches for Protein Structure Classification in Single Particle Analysis | |||||||||||
言語 | ||||||||||||
言語 | jpn | |||||||||||
著者 |
馬水, 信弥
× 馬水, 信弥× 田中, 康太郎× 安永, 卓生
WEKO
7216
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抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | クライオ電子顕微鏡による単粒子解析では,試料中に含まれる複数のタンパク質構造を分類しながら解くことが出来る.ただし分類された構造間のダイナミクスの情報は類推するしかない.この問題について2020年に発表された三次元再構成およびクラス分類を行うための深層学習アプローチであるcryoDRGNは,離散的なデータ分割による構造分類を脱却し,連続的な構造分類を実現した.そこでは,オートエンコーダーをベースとし,入力粒子画像から投影パラメーターに依存する情報を分離して潜在空間を構築している.本稿では従来の構造分類と,cryoDRGNおよびその背景となる深層学習のトピックについて解説を行ったのち,構造分類のベンチマークとして6種類の複合体を有するGroEL/ESの実データについて三次元再構成とその分類を試みた. | |||||||||||
言語 | ja | |||||||||||
抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | Cryo-EM single particle analysis can solve multiple protein structures contained in a sample by classification. However, the information on the dynamics between the solved structures is lost and it can only be inferred. About this problem, cryoDRGN, a deep learning approach for solving the three-dimensional reconstruction and structural classification that was announced in 2020, breaks away from discrete data partition. The method is based on an auto-encoder, and realizes continuous structural classification by constructing a latent space that separates the information depending on the projection parameters from the input particle image. In this paper, we explain conventional classification method in single particle analysis and deep learning topics that are the background of cryoDRGN. Then, as a benchmark for structural classification, we try three-dimensional reconstruction on the actual data of GroEL/ES having 6 kinds of complexes. | |||||||||||
言語 | en | |||||||||||
書誌情報 |
ja : 顕微鏡 巻 55, 号 3, p. 104-108, 発行日 2020-12-30 |
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出版社 | ||||||||||||
言語 | ja | |||||||||||
出版者 | 日本顕微鏡学会 | |||||||||||
DOI | ||||||||||||
関連タイプ | isIdenticalTo | |||||||||||
識別子タイプ | DOI | |||||||||||
関連識別子 | https://doi.org/10.11410/kenbikyo.55.3_104 | |||||||||||
論文ID(NAID) | ||||||||||||
関連タイプ | isIdenticalTo | |||||||||||
識別子タイプ | NAID | |||||||||||
関連識別子 | 130007967723 | |||||||||||
日本十進分類法 | ||||||||||||
主題Scheme | NDC | |||||||||||
主題 | 549 | |||||||||||
NCID | ||||||||||||
収録物識別子タイプ | NCID | |||||||||||
収録物識別子 | AA11917781 | |||||||||||
ISSN | ||||||||||||
収録物識別子タイプ | EISSN | |||||||||||
収録物識別子 | 2434-2386 | |||||||||||
ISSN | ||||||||||||
収録物識別子タイプ | PISSN | |||||||||||
収録物識別子 | 1349-0958 | |||||||||||
著作権関連情報 | ||||||||||||
権利情報 | Copyright (c) 2020 The Japanese Society of Microscopy | |||||||||||
キーワード | ||||||||||||
言語 | ja | |||||||||||
主題Scheme | Other | |||||||||||
主題 | 単粒子解析 | |||||||||||
キーワード | ||||||||||||
言語 | ja | |||||||||||
主題Scheme | Other | |||||||||||
主題 | クラス分類 | |||||||||||
キーワード | ||||||||||||
言語 | ja | |||||||||||
主題Scheme | Other | |||||||||||
主題 | 深層学習 | |||||||||||
キーワード | ||||||||||||
言語 | ja | |||||||||||
主題Scheme | Other | |||||||||||
主題 | オートエンコーダー | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | single particle analysis | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | structural classification of proteins | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | deep learning | |||||||||||
キーワード | ||||||||||||
言語 | en | |||||||||||
主題Scheme | Other | |||||||||||
主題 | auto-encorder | |||||||||||
出版タイプ | ||||||||||||
出版タイプ | VoR | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
査読の有無 | ||||||||||||
値 | yes | |||||||||||
研究者情報 | ||||||||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/266_ja.html | ||||||||||||
論文ID(連携) | ||||||||||||
10361542 | ||||||||||||
連携ID | ||||||||||||
9572 | ||||||||||||
著者別名 | ||||||||||||
姓名 | Mamizu, Nobuya | |||||||||||
著者別名 | ||||||||||||
姓名 | Tanaka, Kotaro | |||||||||||
著者別名 | ||||||||||||
姓名 | Yasunaga, Takuo | |||||||||||
言語 | en | |||||||||||
姓名 | 安永, 卓生 | |||||||||||
言語 | ja | |||||||||||
姓名 | ヤスナガ, タクオ | |||||||||||
言語 | ja-Kana |