NOBUAKI YASUO

Specially Appointed Associate Professor (Lecturer)

Tokyo Institute of Technology

Japan

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About

Nobuaki Yasuo is a Specially Appointed Associate Professor (Lecturer) at Tokyo Institute of Technology, Japan. His research focuses on molecular optimization, drug design, and machine learning applications in chemistry. Recent work includes advancements in reinforcement learning for compound exploration and the development of diffusion models for structure-based drug design. He also investigates the performance of amine solutions for CO2 absorption and conducts toxicokinetic analyses of anticoagulants in bats.

Articles (14)

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2020

Collaborators (7)

Shigeru Kobayashi

Project Assistant Professor

University of Tokyo

JAPAN

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Takashi Ishida

Associate professor

Tokyo Insitute of Technology

JAPAN

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Daniel Ken INAOKA

Associate Professor

Nagasaki University

JAPAN

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Masakazu Sekijima

JAPAN

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Ryo Nakayama

Specially-appointed Assistant Professor

University of Tokyo

JAPAN

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Kazuki Takeda

Assistant professor

Kitasato University

JAPAN

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Yuki Kohno

National Institute of Advanced Industrial Science and Technology (AIST)

JAPAN

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NOBUAKI YASUO

Research Interests

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Articles (14)

DiffInt: A Diffusion Model for Structure-Based Drug Design with Explicit Hydrogen Bond Interaction Guidance

Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning

Prediction of CO2 absorbing performance of amine aqueous solution using random forest models

Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search

IEV2Mol: Molecular Generative Model Considering Protein–Ligand Interaction Energy Vectors

Tuning Bayesian optimization for materials synthesis: simulating two- and three-dimensional cases

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning

Tuning of Bayesian optimization for materials synthesis: simulation of the one-dimensional case

Toxicokinetic analysis of the anticoagulant rodenticides warfarin & diphacinone in Egyptian fruit bats (Rousettus aegyptiacus) as a comparative sensitivity assessment for Bonin fruit bats (Pteropus pselaphon)

Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary Amides

Statistical potentials for RNA-protein interactions optimized by CMA-ES

MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning

Bayesian statistics-based analysis of AC impedance spectra

Collaborators (7)

Shigeru Kobayashi

Takashi Ishida

Daniel Ken INAOKA

Masakazu Sekijima

Ryo Nakayama

Kazuki Takeda

Yuki Kohno

Make your next move.

NOBUAKI YASUO

Research Interests

Explore related searches

Contact this professor

About

Articles (14)

DiffInt: A Diffusion Model for Structure-Based Drug Design with Explicit Hydrogen Bond Interaction Guidance

Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning

Prediction of CO2 absorbing performance of amine aqueous solution using random forest models

Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search

IEV2Mol: Molecular Generative Model Considering Protein–Ligand Interaction Energy Vectors

Tuning Bayesian optimization for materials synthesis: simulating two- and three-dimensional cases

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning

Tuning of Bayesian optimization for materials synthesis: simulation of the one-dimensional case

Toxicokinetic analysis of the anticoagulant rodenticides warfarin &amp; diphacinone in Egyptian fruit bats (Rousettus aegyptiacus) as a comparative sensitivity assessment for Bonin fruit bats (Pteropus pselaphon)

Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary Amides

Statistical potentials for RNA-protein interactions optimized by CMA-ES

MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning

Bayesian statistics-based analysis of AC impedance spectra

Collaborators (7)

Shigeru Kobayashi

Takashi Ishida

Daniel Ken INAOKA

Masakazu Sekijima

Ryo Nakayama

Kazuki Takeda

Yuki Kohno

Make your next move.

Toxicokinetic analysis of the anticoagulant rodenticides warfarin & diphacinone in Egyptian fruit bats (Rousettus aegyptiacus) as a comparative sensitivity assessment for Bonin fruit bats (Pteropus pselaphon)