Nobuaki Yasuo - researchr alias

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Viewing Publication 1 - 7 from 7

2022

An Improved Model for Predicting Compound Retrosynthesizability Using Machine LearningMami Ozawa, Nobuaki Yasuo, Masakazu Sekijima. bibe 2022: 210-216 [doi]

Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary AmidesKazuki Z. Yamamoto, Nobuaki Yasuo, Masakazu Sekijima. jcisd, 62(2):350-358, 2022. [doi]

2021

MERMAID: an open source automated hit-to-lead method based on deep reinforcement learningDaiki Erikawa, Nobuaki Yasuo, Masakazu Sekijima. jcheminf, 13(1):94, 2021. [doi]

2020

Determination of LQR weights by Bayesian optimization method using multiple earthquake wavesKou Miyamoto, Nobuaki Yasuo, Yinli Chen, Daiki Sato, Jinhua She. iecon 2020: 2651-2655 [doi]

2019

Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based LearningNobuaki Yasuo, Masakazu Sekijima. jcisd, 59(3):1050-1061, 2019. [doi]

2018

Compound property enhancement by virtual compound synthesisNaoki Arai, Shunsuke Yoshikawa, Nobuaki Yasuo, Ryunosuke Yoshino, Masakazu Sekijima. jbcb, 16(3):1-13, 2018. [doi]

CoDe-DTI: Collaborative Deep Learning-based Drug-Target Interaction PredictionNobuaki Yasuo, Yusuke Nakashima, Masakazu Sekijima. bibm 2018: 792-797 [doi]

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