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Nobuaki Yasuo
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2020 – today
- 2024
- [j6]Mami Ozawa, Shogo Nakamura, Nobuaki Yasuo, Masakazu Sekijima:
IEV2Mol: Molecular Generative Model Considering Protein-Ligand Interaction Energy Vectors. J. Chem. Inf. Model. 64(18): 6969-6978 (2024) - [j5]Takamasa Suzuki, Dian Ma, Nobuaki Yasuo, Masakazu Sekijima:
Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search. J. Chem. Inf. Model. 64(19): 7291-7302 (2024) - 2022
- [j4]Kazuki Z. Yamamoto, Nobuaki Yasuo, Masakazu Sekijima:
Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary Amides. J. Chem. Inf. Model. 62(2): 350-358 (2022) - [c3]Mami Ozawa, Nobuaki Yasuo, Masakazu Sekijima:
An Improved Model for Predicting Compound Retrosynthesizability Using Machine Learning. BIBE 2022: 210-216 - 2021
- [j3]Daiki Erikawa, Nobuaki Yasuo, Masakazu Sekijima:
MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning. J. Cheminformatics 13(1): 94 (2021) - 2020
- [c2]Kou Miyamoto, Nobuaki Yasuo, Yinli Chen, Daiki Sato, Jinhua She:
Determination of LQR weights by Bayesian optimization method using multiple earthquake waves. IECON 2020: 2651-2655
2010 – 2019
- 2019
- [j2]Nobuaki Yasuo, Masakazu Sekijima:
Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning. J. Chem. Inf. Model. 59(3): 1050-1061 (2019) - 2018
- [j1]Naoki Arai, Shunsuke Yoshikawa, Nobuaki Yasuo, Ryunosuke Yoshino, Masakazu Sekijima:
Compound property enhancement by virtual compound synthesis. J. Bioinform. Comput. Biol. 16(3): 1840016:1-1840016:13 (2018) - [c1]Nobuaki Yasuo, Yusuke Nakashima, Masakazu Sekijima:
CoDe-DTI: Collaborative Deep Learning-based Drug-Target Interaction Prediction. BIBM 2018: 792-797
Coauthor Index
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