Hayashi Shuto

ハヤシシュウト | Hayashi Shuto

Affiliation and department：
Job title： Associate Professor
Homepage URL (1)： http://www.shimamlab.info/

Research field (2)： Biological, health, and medical informatics , Systems genomics

Research keywords (3)： Bioinformatics , Deep Learning , Bayesian Statistics

Research theme for competitive and other funds (4)：

2022 - 2027 深層学習を用いた高速タンパク質構造サンプリング手法の開発
2024 - 2026 マルチモーダル深層アンサンブルと多目的バッチベイズ最適化による分子設計の加速
2023 - 2025 マウス発生休止胚において、再発生能の有無を予測する技術と付与する技術の創出
2022 - 2025 Development of a fast molecular dynamics simulation method using deep learning

Papers (18)：

Chikara Mizukoshi, Yasuhiro Kojima, Satoshi Nomura, Shuto Hayashi, Ko Abe, Teppei Shimamura. DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates. Genome Biology. 2024. 25. 1. 229
Masahiro Hashimoto, Yasuhiro Kojima, Takeharu Sakamoto, Yuki Ozato, Yusuke Nakano, Tadashi Abe, Kiyotaka Hosoda, Hideyuki Saito, Satoshi Higuchi, Yuichi Hisamatsu, et al. Spatial and single-cell colocalisation analysis reveals MDK-mediated immunosuppressive environment with regulatory T cells in colorectal carcinogenesis. eBioMedicine. 2024. 103. 105102-105102
Yasuhiro Kojima, Shinji Mii, Shuto Hayashi, Haruka Hirose, Masato Ishikawa, Masashi Akiyama, Atsushi Enomoto, Teppei Shimamura. Single-cell colocalization analysis using a deep generative model. Cell Systems. 2024. 15. 2. 180-192.e7
Yuta Kobayashi, Atsushi Niida, Satoshi Nagayama, Koichi Saeki, Hiroshi Haeno, Kazuki K. Takahashi, Shuto Hayashi, Yuki Ozato, Hideyuki Saito, Takanori Hasegawa, et al. Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers. British Journal of Cancer. 2023. 129. 7. 1105-1118
Jun Koseki, Shuto Hayashi, Yasuhiro Kojima, Haruka Hirose, Teppei Shimamura. Topological data analysis of protein structure and inter/intra- molecular interaction changes attributable to amino acid mutations. Computational and Structural Biotechnology Journal. 2023. 21. 2950-2959

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MISC (23)：

Matthew H. Bailey, William U. Meyerson, Lewis Jonathan Dursi, Liang-Bo Wang, Guanlan Dong, Wen-Wei Liang, Amila Weerasinghe, Shantao Li, Yize Li, Sean Kelso, M, et al. Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples. Nature Communications. 2020. 11. 1. 4748-4748
Constance H. Li, Stephenie D, Prokopec, Ren X. Sun, Fouad Yousif, Nathaniel Schmitz, PCAWG Tumour Subtypes Clinical Translation, Paul C. Boutros, PCAWG Consortium. Sex differences in oncogenic mutational processes. Nature Communications. 2020. 11. 1. 4330-4330
Sergei Yakneen, Sebastian M. Waszak, PCAWG Technical Working Group, Michael Gertz, Jan O. Korbel, PCAWG Consortium. Butler enables rapid cloud-based analysis of thousands of human genomes. Nature Biotechnology. 2020. 38. 3. 288-292
Bernardo Rodriguez-Martin, Eva G. Alvarez, Adrian Baez-Ortega, Jorge Zamora, Fran Supek, Jonas Demeulemeester, Martin Santamarina, Young Seok Ju, Javier Temes, Daniel Garcia-Souto, et al. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition. Nature Genetics. 2020. 52. 3. 306-319
Kadir C. Akdemir, Victoria T. Le, Sahaana Chandran, Yilong Li, Roel G. Verhaak, Rameen Beroukhim, Peter J. Campbell, Lynda Chin, Jesse R. Dixon, P. Andrew Futreal, et al. Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer. Nature Genetics. 2020. 52. 3. 294-305

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Books (3)：

HLA Typing and Mutation Calling from Normal and Tumor Whole Genome Sequencing Data with ALPHLARD-NT
Humana 2024
Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine Learning.
Humana 2022
論文図表を読む作法 : はじめて出会う実験&解析法も正しく解釈! : 生命科学・医学論文をスラスラ読むためのFigure事典
羊土社 2022 ISBN:9784758122603

Lectures and oral presentations (21)：

AIとロボティクスが拓くタンパク質設計の新時代
(生命情報科学若手の会第15回セミナー 2024)
A framework for enhanced de novo protein design using deep learning and Bayesian optimization
(CBI学会2024年大会 2024)
De novo protein design through integration of deep learning and DBTL cycles
(The 1st Asia & Pacific Bioinformatics Joint Conference 2024)
生成AIとロボットの協働による次世代タンパク質設計
(データサイエンスと生命医科学研究のフロンティア 2024)
Molecular Dynamics Meets Deep Learning: A New Era of Efficient Simulations
(「富岳」成果創出加速プログラム課題生体分子シミュレータを基にした大規模推論システムの開発と応用マンスリーセミナー 2024)

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Education (3)：

2016 - 2019 The University of Tokyo The Graduate School of Information Science and Technology Department of Computer Science Doctoral Course
2014 - 2016 The University of Tokyo The Graduate School of Information Science and Technology Department of Computer Science Master Course
2010 - 2014 The University of Tokyo Faculty of Science Department of Information Science

Professional career (1)：

Work history (6)：

2024/10 - 現在 Institute of Science Tokyo Department of Computational and Systems Biology, Medical Research Laboratory, Institute of Integrated Research Associate Professor
2024/07 - 現在 Kawasaki Institute of Industrial Promotion Innovation Center of NanoMedicine Visiting Scientist
2023/04 - 2024/09 Tokyo Medical and Dental University Department of Computational and Systems Biology, Medical Research Institute Associate Professor
2023/01 - 2023/04 Tokyo Medical and Dental University Department of Computational and Systems Biology, Medical Research Institute Project Associate Professor
2021/04 - 2022/12 Nagoya University Division of Systems Biology, Graduate School of Medicine Designated Associate Professor

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Association Membership(s) (3)：

CBI学会 , International Society for Computational Biology , 日本バイオインフォマティクス学会

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