透析患者を対象とした事前指示書の検討 von 津畑, 豊, 田邊, 繁世, 安城, 淳哉, 津畑, 千佳子, 秋山, 史大

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2. 血液透析歴20年以上の高齢患者の栄養状態と食事摂取状況の実態 von 小林綾子, 武田織枝, 山田礼子, 秋山史大

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31. 急性血液浄化を想定したModalityの差違と血中濃度・浄化効率を考える von 石田俊太郎, 磯野拓郎, 神林晃浩, 佐藤巧, 高井千夏, 大田毅, 秋山史大

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Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations von Sugita, Masatake, Sugiyama, Satoshi, Fujie, Takuya, Yoshikawa, Yasushi, Yanagisawa, Keisuke, Ohue, Masahito, Akiyama, Yutaka

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Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem von Ban, Tomohiro, Ohue, Masahito, Akiyama, Yutaka

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CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides von Li, Jianan, Yanagisawa, Keisuke, Sugita, Masatake, Fujie, Takuya, Ohue, Masahito, Akiyama, Yutaka

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Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations von Sugita, Masatake, Fujie, Takuya, Yanagisawa, Keisuke, Ohue, Masahito, Akiyama, Yutaka

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MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers von Ohue, Masahito, Shimoda, Takehiro, Suzuki, Shuji, Matsuzaki, Yuri, Ishida, Takashi, Akiyama, Yutaka

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Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning von Li, Jianan, Yanagisawa, Keisuke, Yoshikawa, Yasushi, Ohue, Masahito, Akiyama, Yutaka

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MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions von Hayashi, Takanori, Matsuzaki, Yuri, Yanagisawa, Keisuke, Ohue, Masahito, Akiyama, Yutaka

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Taxonomic and Gene Category Analyses of Subgingival Plaques from a Group of Japanese Individuals with and without Periodontitis von Izawa, Kazuki, Okamoto-Shibayama, Kazuko, Kita, Daichi, Tomita, Sachiyo, Saito, Atsushi, Ishida, Takashi, Ohue, Masahito, Akiyama, Yutaka, Ishihara, Kazuyuki

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Interaction Surfaces of Proteins Involved in Bacterial Chemotaxis with Rigid-Body Docking Decoys von Uchikoga, Nobuyuki, Matsuzaki, Yuri, Ohue, Masahito, Akiyama, Yutaka

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Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques von Tajimi, Takashi, Wakui, Naoki, Yanagisawa, Keisuke, Yoshikawa, Yasushi, Ohue, Masahito, Akiyama, Yutaka

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Spresso: an ultrafast compound pre-screening method based on compound decomposition von Yanagisawa, Keisuke, Komine, Shunta, Suzuki, Shogo D, Ohue, Masahito, Ishida, Takashi, Akiyama, Yutaka

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QEX: target-specific druglikeness filter enhances ligand-based virtual screening von Mochizuki, Masahiro, Suzuki, Shogo D., Yanagisawa, Keisuke, Ohue, Masahito, Akiyama, Yutaka

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Cloud Computing for All-To-All Protein-Protein Docking on Azure HPC von Ohue, Masahito, Yamamoto, Yuki, Hayashi, Takanori, Matsuzaki, Yuri, Akiyama, Yutaka

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Learning-to-rank technique based on ignoring meaningless ranking orders between compounds von Ohue, Masahito, Suzuki, Shogo D., Akiyama, Yutaka

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Link Mining for Kernel-Based Compound-Protein Interaction Predictions Using a Chemogenomics Approach von Ohue, Masahito, Yamazaki, Takuro, Ban, Tomohiro, Akiyama, Yutaka

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Effective Protein–Ligand Docking Strategy via Fragment Reuse and a Proof-of-Concept Implementation von Yanagisawa, Keisuke, Kubota, Rikuto, Yoshikawa, Yasushi, Ohue, Masahito, Akiyama, Yutaka

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Improved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets von Takabatake, Kazuki, Izawa, Kazuki, Akikawa, Motohiro, Yanagisawa, Keisuke, Ohue, Masahito, Akiyama, Yutaka

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