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Author

Manato Akiyama

Observed name: Akiyama, Manato
Institution: Kitasato University
ORCID: 0000-0002-5177-3199
Observed ORCID: 0000-0002-5177-3199
OpenAlex ID: A5082419201
RNA secondary structure prediction using deep learning with thermodynamic integration
2021 · Kengo Sato, Manato Akiyama, et al. · Nature Communications · 469
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Informative RNA base embedding for RNA structural alignment and clustering by deep representation learning
2022 · Manato Akiyama, Yasubumi Sakakibara · NAR Genomics and Bioinformatics · 138
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Variational autoencoder-based chemical latent space for large molecular structures with 3D complexity
2023 · Toshiki Ochiai, Tensei Inukai, et al. · Communications Chemistry · 97
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A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model
2018 · Manato Akiyama, Kengo Sato, et al. · Journal of Bioinformatics and Computational Biology · 57
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Deep learning of multimodal networks with topological regularization for drug repositioning
2024 · Yuto Ohnuki, Manato Akiyama, et al. · Journal of Cheminformatics · 16
Direct Inference of Base-Pairing Probabilities with Neural Networks Improves Prediction of RNA Secondary Structures with Pseudoknots
2022 · Manato Akiyama, Yasubumi Sakakibara, et al. · Genes · 10
Leveraging tree-transformer VAE with fragment tokenization for high-performance large chemical model generation
2025 · Tensei Inukai, Aoi Yamato, et al. · Communications Chemistry · 7
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Generative AI-driven artificial DNA design for enhancing inter-species gene activation and enzymatic degradation of PET
2025 · Manato Akiyama, Motohiko Tashiro, et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2
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A Tree-Transformer based VAE with fragment tokenization for large chemical models
2024 · Tensei Inukai, Aoi Yamato, et al. · ChemRxiv · 2
A Tree-Transformer based VAE with fragment tokenization for large chemical models
2024 · Tensei Inukai, Aoi Yamato, et al. · ChemRxiv · 2
RNA Secondary Structure Prediction Based on Energy Models
2023 · Manato Akiyama, Kengo Sato · Methods in molecular biology · 2
Genomic style: yet another deep-learning approach to characterize bacterial genome sequences
2021 · Yuka Yoshimura, Akifumi Hamada, et al. · Bioinformatics Advances · 2
Cross-species gene redesign leveraging ortholog information and generative modeling
2026 · Manato Akiyama, Motohiko Tashiro, et al. · Nature Communications · 1
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RIFT-VAE: grammar-conditioned pretraining and latent-space optimization for RNA inverse folding
2026 · Kentaro Watanabe, Manato Akiyama, et al. · bioRxiv (Cold Spring Harbor Laboratory)
Reinforcement Learning Based Design of Protein-binding RNA Sequences
2026 · Ayuka Ishii, Manato Akiyama, et al. · IPSJ Transactions on Bioinformatics
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RNA secondary structure prediction using deep learning with thermodynamic integration
2025 · 佐藤健吾, Kengo Sato, et al. · Tokyo Tech Research Repository (Tokyo Institute of Technology)
Leveraging Tree-Transformer VAE with fragment tokenization for high-performance large chemical generative model
2024 · Tensei Inukai, Aoi Yamato, et al. · ChemRxiv
Deep generative model of constructing chemical latent space for large molecular structures with 3D complexity
2023 · Toshiki Ochiai, Tensei Inukai, et al. · ChemRxiv
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Deep generative model of constructing chemical latent space for small to large molecular structures with 3D complexity
2023 · Toshiki Ochiai, Tensei Inukai, et al. · ChemRxiv
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Development of RNA informatics for RNA sequence and structure analysis (本文)
2021 · アキヤマ, マナト, Akiyama, Manato, et al. · KeiO Associated Repository of Academic Resources (Keio University)
Development of RNA informatics for RNA sequence and structure analysis (審査報告)
2021 · アキヤマ, マナト, Akiyama, Manato, et al. · KeiO Associated Repository of Academic Resources (Keio University)
Development of RNA informatics for RNA sequence and structure analysis (要旨)
2021 · アキヤマ, マナト, Akiyama, Manato, et al. · KeiO Associated Repository of Academic Resources (Keio University)
Direct inference of base-pairing probabilities with neural networks improves RNA secondary structure prediction with pseudoknots
2018 · Manato Akiyama, Yasubumi Sakakibara, et al. · bioRxiv (Cold Spring Harbor Laboratory)
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Works count: 23
Citation count: 805
H-index: 7
I10-index: 6
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