Institute of Science Tokyo · School of Life Science and Technology · 助教

Research keywordsRNA structure prediction・RNA 5-methylcytosine・DNA N6-methyladenine・human-virus protein-protein interactions・drug-target interaction prediction・peptide bioactivity prediction・deep learning in bioinformatics

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• DRfold2 is a deep learning-based tool that enables efficient and accurate RNA structure prediction2026 · PLOS Biology 24 ( 2 ) e3003659 - e3003659 2026年2月
• PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides.2024 · PloS one 19 ( 8 ) e0309078 2024年
• MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.2024 · Methods (San Diego, Calif.) 227 37 - 47 2024年7月
• CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction.2023 · Computational and structural biotechnology journal 21 644 - 654 2023年

• RNAの複数の安定立体構造と平衡分布を予測する革新的拡散モデルの開発2025 · 研究課題/領域番号： 25K24407 2025年7月 - 2027年3月
• 革新的AIによるヒト-ウイルスタンパク質間相互作用阻害剤の予測2023 · 研究課題/領域番号： 22KJ2495 2023年3月 - 2025年3月

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