International Conferences (Oral)

    2019

  1. Tomoei Takahashi, George Chikenji, and Kei Tokita
    "Protein design using Bayesian learning"
    7th CIJK MB, Beijing, Aug. 2019.

Domestic Conferences (Oral)

    2022

  1. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「Cavity 法によタンパク質デザイン」
    ("Lattice protein design using the cavity method")
    JPS Fall Meeting, Tokyo Institute of Technology, Sep. 2022.

  2. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「Cavity 法による格子タンパク質模型のデザイン」
    ("Lattice protein design using the cavity method")
    77th JPS Meeting, Online, Mar. 2022.

    3. 2021

  3. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「水の効果を外場とした格子タンパク質の経験ベイズ法によるデザイン」
    ("Protein Design by Empirical Bayes' Method")
    76th JPS meeting, Online, Mar. 2021.

  4. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「Miyazawa-Jernigan 行列をエネルギーパラメータとしたベイズ学習による格子タンパク質デザイン」
    ("Lattice protein design using Bayesian Learning with Miyazawa-Jernigan energy matrix")
    JPS Fall Meeting, Online, Sep. 2021.

    5. 2020

  5. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「経験ベイズ推定を用いた水の効果の最適化によるタンパク質デザイン」
    ("Protein design by optimization of role of water using empirical Bayes' estimation")
    JPS Fall meeting, Online, Sep. 2020.

  6. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「経験ベイズ推定による格子タンパク質模型のデザイン」
    ("Lattice protein design using empirical Bayes estimation")
    75th JPS meeting, Nagoya, Mar. 2020.

    7. 2019

  7. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「相互作用グラフの特徴を考慮したベイズ学習によるタンパク質デザイン」
    ("Protein design by Bayesian machine learning considering its interaction graph")
    JPS Fall meeting, Gifu, Sep. 2019.

  8. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「ベイズ学習による格子タンパク質模型のデザイン」
    ("Design of lattice protein model using Bayesian machine learning")
    74th JPS meeting, Fukuoka, Mar. 2019.

International Conferences (Poster)

    2022

  1. Tomoei Takahashi, George Chikenji, and Kei Tokita
    ("The cavity method to protein design problem")
    Roles of heterogeneity in non-equilibrium collective dynamics (RHINO 2022)
    Hongo Campus, The University of Tokyo, September, 2022

Domestic Conferences (Poster)

    2022

  1. Tomoei Takahashi, George Chikenji, and Kei Tokita
    ("Lattice protein design using Bayesian learning")
    「ベイズ学習による格子タンパク質模型のデザイン」
    The 60th Annual Meeting of the BSJ, Hakodate, Hokkaido, Sep. 2022.
    第60回日本生物物理学会年会 (2022年9月)

Seminers

    2021

  1. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「ベイズ学習による格子タンパク質模型のデザイン」
    ("Lattice protein design using Bayesian learning")
    Macoto Kikuchi's Group Seminer, Cybermedia Center, Osaka University, Online, Jul. 2021.

  2. Tomoei Takahashi, George Chikenji, and Kei Tokita
    「Cavity 法による格子タンパク質模型のデザイン」
    ("Cavity Method to the lattice protein problem")
    Mathematical Information Systems Group, Department of Systems Science,
    Graduate School of iInformatics, Kyoto University, Nov. 2021.