Refereed Papers
2021
- Tomoei Takahashi, George Chikenji, and Kei Tokita
"Lattice protein design using Bayesian learning"
Physical Review E 104, 014404 (Published 8 July, 2021)
arXiv:2003.06601
Nagoya University Press Release (In Japanese)
2022
- [in Japanese & in print only] 高橋智栄, 千見寺浄慈, 時田恵一郎
「ベイズ学習による格子タンパク質模型のデザイン」
学会誌「シミュレーション」, 最先端研究, Vol. 41, No.3, pp.30-35, 2022
(2022年9月号). - Tomoei Takahashi, George Chikenji, and Kei Tokita
"The cavity method to protein design problem"
Jounal of Statistical Mechanics: Theory and Experiment,103403 (Published 12 October, 2022)
arXiv:2205.03696
Nagoya University Press Release (In Japanese)
2025
- [in Japanese] 高橋智栄, 千見寺浄慈, 時田恵一郎
「タンパク質デザインの統計力学」
日本物理学会誌 最近の研究から Vol 80, No. 3, pp.116-120, 2025
DOI: 10.11316/butsuri.80.3_116
(2025年3月号).
- Tomoei Takahashi, George Chikenji, Kei Tokita, and Yoshiyuki Kabashima
"Alpha helices are more evolutionarily robust to environmental perturbations than beta sheets: Bayesian learning and statistical mechanics for protein evolution"
Physical Review Research 7, 023115
(Published 5 May, 2025)
arXiv:2409.03297
「タンパク質デザインの統計力学」
日本物理学会誌 最近の研究から Vol 80, No. 3, pp.116-120, 2025
DOI: 10.11316/butsuri.80.3_116 (2025年3月号).
"Alpha helices are more evolutionarily robust to environmental perturbations than beta sheets: Bayesian learning and statistical mechanics for protein evolution"
Physical Review Research 7, 023115 (Published 5 May, 2025)
arXiv:2409.03297