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Kai Shimagaki
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Cited by
Year
Selection of sequence motifs and generative Hopfield-Potts models for protein families
K Shimagaki, M Weigt
Physical Review E 100 (3), 032128, 2019
352019
Sparse generative modeling via parameter reduction of Boltzmann machines: application to protein-sequence families
P Barrat-Charlaix*, AP Muntoni, K Shimagaki, M Weigt, F Zamponi
Physical Review E 104 (2), 024407, 2021
222021
Sparse generative modeling of protein-sequence families
P Barrat-Charlaix, AP Muntoni, K Shimagaki, M Weigt, F Zamponi
arXiv e-prints, arXiv: 2011.11259, 2020
42020
Bézier interpolation improves the inference of dynamical models from data
K Shimagaki, JP Barton
Physical Review E 107 (2), 024116, 2023
32023
Collective-variable selection and generative Hopfield-Potts models for protein-sequence families
K Shimagaki, M Weigt
bioRxiv, 652784, 2019
32019
Detectability of epistasis from temporal genetic data
K Shimagaki, J Barton
Bulletin of the American Physical Society, 2024
2024
Inferring epistasis for HIV evolution
K Shimagaki, J Barton
APS March Meeting Abstracts 2023, Y08. 006, 2023
2023
Non-linear interpolation for genetic fitness prediction
K Shimagaki, J Barton
APS March Meeting Abstracts 2022, A06. 011, 2022
2022
Advanced statistical modeling and variable selection for protein sequences
K Shimagaki
Sorbonne Université, 2021
2021
Campagne 2020 Contrats Doctoraux Instituts/Initiatives
K Shimagaki, M Muscat
2020
Selection of sequence motifs and generative Hopfield-Potts models for protein familiesilies
K Shimagaki, M Weigt
arXiv preprint arXiv:1905.11848, 2019
2019
スパース性を仮定したアミノ酸残基間の直接相関推定
島垣凱
日本物理学会講演概要集 74.2, 2310-2310, 2019
2019
低ランクモデルを用いたアミノ酸残基の直接相関推定
K Shimagaki, M Weigt
日本物理学会, 2018
2018
Contrastive Divergenceにおける系統的バイアスの遷移確率依存性の解析
凱島垣, 眞治藤堂
日本物理学会, 2017
2017
Minimum Probability Flowを用いたイジング模型のモデルパラメータ推定と、遷移確率の依存性の解析
凱島垣, 眞治藤堂
日本物理学会, 2016
2016
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Articles 1–15