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秋山泰 2020年 研究業績一覧 (23件 / 583件)
論文
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Fujimoto K,
Kimura Y,
Shimohigoshi M,
Satoh T,
Sato S,
Tremmel G,
Uematsu M,
Kawaguchi Y,
Usui Y,
Hayashi T,
Kashima K,
Yuki Y,
Furukawa Y,
Kakuta M,
Yutaka Akiyama,
Yamaguchi R,
Crowe SE,
Ernst PB,
Miyano S,
Kiyono H,
Imoto S,
Uematsu S.
Data on Intestinal Phage-Bacteria Associations Aids the Development of Phage Therapy against Pathobionts,
Cell Host & Microbe,
Elsevier,
Volume 28,
Issue 3,
Page 380-389,
Sept. 2020.
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Aizhen Ren,
Takashi Ishida,
Yutaka Akiyama.
Mathematical proof of the third order accuracy of the speedy double botstrap method,
Communication in Statistics-Theory and Methods,
Taylor & Francis,
Vol. 49,
issue 16,
pp. 3950-3964,
Aug. 2020.
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Izawa K,
Kubosaki A,
Kobayashi N,
Akiyama Y,
Yamazaki A,
Hashimoto K,
Konuma R,
Kamata Y,
Hara-Kudo Y,
Hasegawa K,
Ikaga T,
Watanabe M.
Comprehensive Fungal Community Analysis of House Dust Using Next-Generation Sequencing,
International Journal of Environmental Research and Public Health,
Volume 17,
Issue 16,
5842,
Aug. 2020.
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Shumpei Matsuno,
Masahito Ohue,
Yutaka Akiyama.
Multidomain protein structure prediction using information about residues interacting on multimeric protein interfaces,
Biophysics and Physicobiology,
Vol. 17,
pp. 2-13,
Jan. 2020.
公式リンク
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Kento Aoyama,
Masanori Kakuta,
Yuri Matsuzaki,
Takashi Ishida,
Masahito Ohue,
Yutaka Akiyama.
Development of computational pipeline software for genome/exome analysis on the K computer,
Supercomputing Frontiers and Innovations,
Vol. 7,
No. 1,
pp. 37-54,
2020.
公式リンク
国際会議発表 (査読有り)
国際会議発表 (査読なし・不明)
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Kazuki Izawa,
K Shibayama,
Masahito Ohue,
Takashi Ishida,
Kazuyuki Ishihara,
Yutaka Akiyama.
The shifts in bacterial community and gene category composition between healthy sites and periodontal disease sites,
The 5th IITM-Tokyo Tech Joint Symposium-Current trends in Bioinformatics: Big data analysis, machine learning and drug design,
Mar. 2020.
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Yuki Tsushima,
Masahito Ohue,
Yutaka Akiyama.
Development of fragment linking method for beyond rule of five,
The 5th IITM-Tokyo Tech Joint Symposium-Current trends in Bioinformatics: Big data analysis, machine learning and drug design,
Mar. 2020.
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Masaya Inagaki,
Masahito Ohue,
Yutaka Akiyama.
Fragment Linking with DQN,
The 5th IITM-Tokyo Tech Joint Symposium-Current trends in Bioinformatics: Big data analysis, machine learning and drug design,
Mar. 2020.
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Takuya Fujie,
Masatake Sugita,
Satoshi Sugiyama,
Yasushi Yoshikawa,
Masahito Ohue,
Yutaka Akiyama.
Conformational Sampling with Molecular Dynamics Simulation for Prediction of Membrane Permeability of Cyclic Peptide,
The 5th IITM-Tokyo Tech Joint Symposium-Current trends in Bioinformatics: Big data analysis, machine learning and drug design,
Mar. 2020.
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Masahito Ohue,
Shogo D. Suzuki,
Yutaka Akiyama.
PKRank & SPDRank - Learning-to-rank methods for machine-learning-based drug discovery,
Biophysical Society 64th Annual Meeting,
Feb. 2020.
公式リンク
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Satoshi Sugiyama,
Yasushi Yoshikawa,
Masahito Ohue,
Yutaka Akiyama.
Development of Membrane Permeability Prediction System for Cyclic Peptide: Large-Scale Molecular Dynamics Simulations,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
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Hiroki Watanabe,
Masahito Ohue,
Yutaka Akiyama.
Exhaustive protein-protein interaction prediction using MEGADOCK on a large-scale HPC environment,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
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Shunpei Matsuno,
Masahito Ohue,
Yutaka Akiyama.
Multidomain protein structure prediction using information about residues interacting on multimeric protein interfaces,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
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Li Jianan,
Yasushi Yoshikawa,
Masahito Ohue,
Yutaka Akiyama.
Prediction of plasma protein binding for cyclic peptides by deep learning and molecular docking,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
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Max Druyvesteyn,
Masahito Ohue,
Yutaka Akiyama.
Improved protein-protein docking using arbitrary docking-derived protein interface predictions,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
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Kento Aoyama,
Hiroki Watanabe,
Masahito Ohue,
Yutaka Akiyama.
Multiple HPC Environments-Aware Container Image Configuration Workflow for Large-Scale All-to-All Protein-Protein Docking Calculations,
2nd RWBC-OIL Workshop,
Jan. 2020.
公式リンク
国内会議発表 (査読なし・不明)
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大上雅史,
青山建人,
秋山泰.
GPUスパコンによる細胞スケールのタンパク質間相互作用予測,
生命情報科学若手の会第12回研究会,
Aug. 2020.
公式リンク
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Masahito Ohue,
Kento Aoyama,
Yutaka Akiyama.
High-performance cloud computing for exhaustive protein-protein docking,
IPSJ Technical Report,
Vol. 2020-MPS-129,
No. 6,
pp. 1-4,
July 2020.
公式リンク
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久保田陸人,
柳澤渓甫,
吉川寧,
大上雅史,
秋山泰.
共通な部分構造の再利用による高速なタンパク質リガンドドッキング手法の開発,
情報処理学会研究報告,
Vol. 2020-BIO-61,
No. 4,
pp. 1-8,
Mar. 2020.
公式リンク
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高畠和輝,
伊澤和輝,
秋川元宏,
大上雅史,
秋山泰.
圧縮アミノ酸を利用した二段階のシード探索によるメタゲノム配列相同性検索の改良,
研究報告バイオ情報学(BIO),
Vol. 2020-BIO-61,
No. 10,
pp. 1-6,
Mar. 2020.
公式リンク
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渡辺紘生,
大上雅史,
秋山泰.
マルチノード・マルチGPU上での網羅的なタンパク質間相互作用予測の高速化,
情報処理学会研究報告,
情報処理学会,
Vol. 2020-BIO-61,
No. 3,
pp. 1-8,
Mar. 2020.
公式リンク
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村田翔太朗,
山田雄太,
吉川寧,
大上雅史,
秋山泰.
二次元分子記述子を用いた機械学習による環状ペプチドの細胞膜透過性予測,
研究報告バイオ情報学(BIO),
情報処理学会,
Vol. 2020-BIO-61,
No. 5,
pp. 1-7,
Mar. 2020.
公式リンク
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