| 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 | 84 | 2021 |
| kGCN: a graph-based deep learning framework for chemical structures R Kojima, S Ishida, M Ohta, H Iwata, T Honma, Y Okuno Journal of Cheminformatics 12, 1-10, 2020 | 82 | 2020 |
| 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 | 78 | 2019 |
| AI-driven synthetic route design incorporated with retrosynthesis knowledge S Ishida, K Terayama, R Kojima, K Takasu, Y Okuno Journal of chemical information and modeling 62 (6), 1357-1367, 2022 | 35 | 2022 |
| CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration R Shibukawa, S Ishida, K Yoshizoe, K Wasa, K Takasu, Y Okuno, K Terayama, K ... Journal of Cheminformatics 12 (52), 2020 | 34 | 2020 |
| Selective inhibitor design for kinase homologs using multiobjective Monte Carlo tree search T Yoshizawa, S Ishida, T Sato, M Ohta, T Honma, K Terayama Journal of Chemical Information and Modeling 62 (22), 5351-5360, 2022 | 11 | 2022 |
| ChemTSv2: Functional molecular design using de novo molecule generator S Ishida, T Aasawat, M Sumita, M Katouda, T Yoshizawa, K Yoshizoe, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 13 (6), e1680, 2023 | 10 | 2023 |
| Design of antimicrobial peptides containing non-proteinogenic amino acids using multi-objective Bayesian optimisation Y Murakami, S Ishida, Y Demizu, K Terayama Digital Discovery 2 (5), 1347-1353, 2023 | 10 | 2023 |
| Deep Learning-Based Differential Diagnosis of Follicular Thyroid Tumors Using Histopathological Images S Nojima, T Kadoi, A Suzuki, C Kato, S Ishida, K Kido, K Fujita, Y Okuno, ... Modern Pathology 36 (11), 100296, 2023 | 6 | 2023 |
| Predicting condensate formation of protein and RNA under various environmental conditions KY Chin, S Ishida, Y Sasaki, K Terayama BMC bioinformatics 25 (1), 143, 2024 | 3 | 2024 |
| AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data Y Shimizu, M Ohta, S Ishida, K Terayama, M Osawa, T Honma, K Ikeda Journal of Cheminformatics 15 (1), 120, 2023 | 3 | 2023 |
| A novel three-dimensional imaging system based on polysaccharide staining for accurate histopathological diagnosis of inflammatory bowel diseases S Nojima, S Ishida, K Terayama, K Matsumoto, T Matsui, S Tahara, ... Cellular and Molecular Gastroenterology and Hepatology 14 (4), 905-924, 2022 | 3 | 2022 |
| GCN-Based Structure-Activity Relationship and DFT Studies of Staphylococcus aureus FabI Inhibitors GC Veríssimo, VS dos Santos Junior, PO Fernandes, S Ishida, R Kojima, ... International Journal of Quantitative Structure-Property Relationships …, 2022 | 2 | 2022 |
| Combining three-dimensional acoustic coring and a convolutional neural network to quantify species contributions to benthic ecosystems K Mizuno, K Terayama, S Ishida, JA Godbold, M Solan Royal Society Open Science 11 (6), 240042, 2024 | 1 | 2024 |
| Large Language Models Open New Way of AI-Assisted Molecule Design for Chemists S Ishida, T Sato, T Honma, K Terayama | 1 | 2024 |
| Quantitative analysis of protein dynamics using a deep learning technique combined with experimental cryo-EM density data and MD simulations S Matsumoto, S Ishida, K Terayama, Y Okuno Biophysics and Physicobiology 20 (2), e200022, 2023 | 1 | 2023 |
| Complex network prediction using deep learning Y Tanaka, R Kojima, S Ishida, F Yamashita, Y Okuno arXiv preprint arXiv:2104.03871, 2021 | 1 | 2021 |
| Development of a method for estimating asari clam distribution by combining three-dimensional acoustic coring system and deep neural network T Kadoi, K Mizuno, S Ishida, S Onozato, H Washiyama, Y Uehara, Y Saito, ... Scientific Reports 14 (1), 26467, 2024 | | 2024 |
| Avoiding Reward Hacking in Multi-Objective Molecular Design: A Data-Driven Generative Strategy with a Reliable Design Framework T Yoshizawa, S Ishida, T Sato, M Ohta, T Honma, K Terayama | | 2024 |
| 深層学習と木探索に基づく de novo 分子設計 石田祥一， 吉澤竜哉， 寺山慧 構造活性相関部会ニュースレター SAR News 44, 1-7, 2023 | | 2023 |
Kei TerayamaYokohama City University確認したメール アドレス: yokohama-cu.ac.jp
