Kei Terayama
Title
Cited by
Cited by
Year
ChemTS: an efficient python library for de novo molecular generation
X Yang, J Zhang, K Yoshizoe, K Terayama, K Tsuda
Science and technology of advanced materials 18 (1), 972-976, 2017
1342017
Population-based de novo molecule generation, using grammatical evolution
N Yoshikawa, K Terayama, M Sumita, T Homma, K Oono, K Tsuda
Chemistry Letters 47 (11), 1431-1434, 2018
412018
Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional Networks
S Ishida, K Terayama, R Kojima, K Takasu, Y Okuno
Journal of chemical information and modeling 59 (12), 5026-5033, 2019
222019
Machine learning accelerates MD-based binding pose prediction between ligands and proteins
K Terayama, H Iwata, M Araki, Y Okuno, K Tsuda
Bioinformatics 34 (5), 770-778, 2018
182018
Efficient construction method for phase diagrams using uncertainty sampling
K Terayama, R Tamura, Y Nose, H Hiramatsu, H Hosono, Y Okuno, ...
Physical Review Materials 3 (3), 033802, 2019
152019
Integration of sonar and optical camera images using deep neural network for fish monitoring
K Terayama, K Shin, K Mizuno, K Tsuda
Aquacultural Engineering 86, 102000, 2019
142019
Fine-grained optimization method for crystal structure prediction
K Terayama, T Yamashita, T Oguchi, K Tsuda
npj Computational Materials 4 (1), 32, 2018
132018
Extraction of protein dynamics information from cryo-EM maps using deep learning
S Matsumoto, S Ishida, M Araki, T Kato, K Terayama, Y Okuno
Nature Machine Intelligence 3 (2), 153-160, 2021
122021
Deep-learning-based quality filtering of mechanically exfoliated 2D crystals
Y Saito, K Shin, K Terayama, S Desai, M Onga, Y Nakagawa, YM Itahashi, ...
npj Computational Materials 5 (1), 1-6, 2019
122019
Enhancing Biomolecular Sampling with Reinforcement Learning: A Tree Search Molecular Dynamics Simulation Method
K Shin, DP Tran, K Takemura, A Kitao, K Terayama, K Tsuda
ACS omega 4 (9), 13853-13862, 2019
122019
Multiple fish tracking with an NACA airfoil model for collective behavior analysis
K Terayama, H Habe, M Sakagami
IPSJ Transactions on Computer Vision and Applications 8 (1), 1-7, 2016
112016
Appearance-based multiple fish tracking for collective motion analysis
K Terayama, K Hongo, H Habe, M Sakagami
2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 361-365, 2015
102015
Efficient recommendation tool of materials by an executable file based on machine learning
K Terayama, K Tsuda, R Tamura
Japanese Journal of Applied Physics 58 (9), 098001, 2019
92019
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration
R Shibukawa, S Ishida, K Yoshizoe, K Wasa, K Takasu, Y Okuno, ...
Journal of cheminformatics 12 (1), 1-14, 2020
82020
Pushing property limits in materials discovery via boundless objective-free exploration
K Terayama, M Sumita, R Tamura, DT Payne, MK Chahal, S Ishihara, ...
Chemical science 11 (23), 5959-5968, 2020
82020
NMR-TS: de novo molecule identification from NMR spectra
J Zhang, K Terayama, M Sumita, K Yoshizoe, K Ito, J Kikuchi, K Tsuda
Science and Technology of Advanced Materials 21 (1), 552-561, 2020
72020
Black-Box Optimization for Automated Discovery
K Terayama, M Sumita, R Tamura, K Tsuda
Accounts of Chemical Research 54 (6), 1334-1346, 2021
62021
A measurement method for speed distribution of collective motion with optical flow and its application to estimation of rotation curve
K Terayama, H Hioki, MA Sakagami
2014 IEEE International Symposium on Multimedia, 32-39, 2014
62014
evERdock BAI: Machine-learning-guided selection of protein-protein complex structure
K Terayama, A Shinobu, K Tsuda, K Takemura, A Kitao
The Journal of Chemical Physics 151 (21), 215104, 2019
52019
Improving the Accuracy of Protein‐Ligand Binding Mode Prediction Using a Molecular Dynamics‐Based Pocket Generation Approach
M Araki, H Iwata, B Ma, A Fujita, K Terayama, Y Sagae, F Ono, K Tsuda, ...
Journal of Computational Chemistry 39 (32), 2679-2689, 2018
52018
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Articles 1–20