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Shuto Hayashi

Showing results (1-10 of 27) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|November 8, 2022
Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine LearningShuto Hayashi, Shumpei Ishikawa
Methods in Molecular Biology (Clifton, N.J.)|June 22, 2024
HLA Typing and Mutation Calling from Normal and Tumor Whole Genome Sequencing Data with ALPHLARD-NTShuto Hayashi, Seiya Imoto
Computational and Structural Biotechnology Journal|December 5, 2022
Bayesian statistical method for detecting structural and topological diversity in polymorphic proteinsShuto Hayashi, Jun Koseki, Teppei Shimamura
Brazilian Journal of Otorhinolaryngology|June 12, 2023
Thyroid metastasis from cervical carcinomaShuto Hayashi, Takumi Kumai, Tomohiko Michizuka, et al.
Computational and Structural Biotechnology Journal|May 25, 2023
Topological data analysis of protein structure and inter/intra-molecular interaction changes attributable to amino acid mutationsJun Koseki, Shuto Hayashi, Yasuhiro Kojima, et al.
Cell Reports Methods|June 5, 2026
Unsupervised deep learning enables blur-free resolution enhancement in two-photon microscopyHaruhiko Morita, Shuto Hayashi, Takahiro Tsuji, et al.
Auris, Nasus, Larynx|February 10, 2023
Internal carotid artery dissection caused by elongated styloid processShuto Hayashi, Takumi Kumai, Kan Kishibe, et al.
Genome Biology|September 5, 2024
DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation ratesChikara Mizukoshi, Yasuhiro Kojima, Satoshi Nomura, et al.
Bioinformatics (Oxford, England)|March 30, 2019
A Bayesian model integration for mutation calling through data partitioningTakuya Moriyama, Seiya Imoto, Shuto Hayashi, et al.
Bioinformatics (Oxford, England)|December 22, 2025
scSurv: a deep generative model for single-cell survival analysisChikara Mizukoshi, Yasuhiro Kojima, Shuto Hayashi, et al.
Pageof 3

Showing results (1-10 of 27) with videos related to

Sort By:
Pageof 3
Methods in Molecular Biology (Clifton, N.J.)|November 8, 2022
Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine LearningShuto Hayashi, Shumpei Ishikawa
Methods in Molecular Biology (Clifton, N.J.)|June 22, 2024
HLA Typing and Mutation Calling from Normal and Tumor Whole Genome Sequencing Data with ALPHLARD-NTShuto Hayashi, Seiya Imoto
Computational and Structural Biotechnology Journal|December 5, 2022
Bayesian statistical method for detecting structural and topological diversity in polymorphic proteinsShuto Hayashi, Jun Koseki, Teppei Shimamura
Brazilian Journal of Otorhinolaryngology|June 12, 2023
Thyroid metastasis from cervical carcinomaShuto Hayashi, Takumi Kumai, Tomohiko Michizuka, et al.
Computational and Structural Biotechnology Journal|May 25, 2023
Topological data analysis of protein structure and inter/intra-molecular interaction changes attributable to amino acid mutationsJun Koseki, Shuto Hayashi, Yasuhiro Kojima, et al.
Cell Reports Methods|June 5, 2026
Unsupervised deep learning enables blur-free resolution enhancement in two-photon microscopyHaruhiko Morita, Shuto Hayashi, Takahiro Tsuji, et al.
Auris, Nasus, Larynx|February 10, 2023
Internal carotid artery dissection caused by elongated styloid processShuto Hayashi, Takumi Kumai, Kan Kishibe, et al.
Genome Biology|September 5, 2024
DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation ratesChikara Mizukoshi, Yasuhiro Kojima, Satoshi Nomura, et al.
Bioinformatics (Oxford, England)|March 30, 2019
A Bayesian model integration for mutation calling through data partitioningTakuya Moriyama, Seiya Imoto, Shuto Hayashi, et al.
Bioinformatics (Oxford, England)|December 22, 2025
scSurv: a deep generative model for single-cell survival analysisChikara Mizukoshi, Yasuhiro Kojima, Shuto Hayashi, et al.
Pageof 3