Hasil Pencarian - Satoru Miyano

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  1. 1
    Computational Tactics for Precision Cancer Network Biology

    Computational Tactics for Precision Cancer Network Biology oleh Heewon Park, Satoru Miyano

    Diterbitkan 2022-11-01
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  2. 2
    Sparse spectral graph analysis and its application to gastric cancer drug resistance-specific molecular interplays identification.

    Sparse spectral graph analysis and its application to gastric cancer drug resistance-specific molecular interplays identification. oleh Heewon Park, Satoru Miyano

    Diterbitkan 2024-01-01
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  3. 3
    Differential Gene Regulatory Network Analysis between Azacitidine-Sensitive and -Resistant Cell Lines

    Differential Gene Regulatory Network Analysis between Azacitidine-Sensitive and -Resistant Cell Lines oleh Heewon Park, Satoru Miyano

    Diterbitkan 2024-03-01
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  4. 4
    Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization.

    Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization. oleh Atsushi Niida, Takanori Hasegawa, Satoru Miyano

    Diterbitkan 2019-01-01
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  5. 5
    Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identification.

    Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identification. oleh Heewon Park, Seiya Imoto, Satoru Miyano

    Diterbitkan 2023-01-01
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  6. 6
    PredictiveNetwork: predictive gene network estimation with application to gastric cancer drug response-predictive network analysis

    PredictiveNetwork: predictive gene network estimation with application to gastric cancer drug response-predictive network analysis oleh Heewon Park, Seiya Imoto, Satoru Miyano

    Diterbitkan 2022-08-01
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  7. 7
    Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets.

    Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets. oleh Heewon Park, Seiya Imoto, Satoru Miyano

    Diterbitkan 2015-01-01
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  8. 8
    Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identification

    Comprehensive information-based differential gene regulatory networks analysis (CIdrgn): Application to gastric cancer and chemotherapy-responsive gene network identification oleh Heewon Park, Seiya Imoto, Satoru Miyano

    Diterbitkan 2023-01-01
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  9. 9
    Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

    Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker. oleh Heewon Park, Teppei Shimamura, Satoru Miyano, Seiya Imoto

    Diterbitkan 2014-01-01
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  10. 10
    A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures.

    A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures. oleh Yuichi Shiraishi, Georg Tremmel, Satoru Miyano, Matthew Stephens

    Diterbitkan 2015-12-01
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  11. 11
    Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

    Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks. oleh Heewon Park, Rui Yamaguchi, Seiya Imoto, Satoru Miyano

    Diterbitkan 2022-01-01
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  12. 12
    Meta graphical lasso: uncovering hidden interactions among latent mechanisms

    Meta graphical lasso: uncovering hidden interactions among latent mechanisms oleh Koji Maruhashi, Hisashi Kashima, Satoru Miyano, Heewon Park

    Diterbitkan 2024-08-01
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  13. 13
    Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers.

    Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers. oleh Yao-Zhong Zhang, Seiya Imoto, Satoru Miyano, Rui Yamaguchi

    Diterbitkan 2021-10-01
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  14. 14
    Global gene network exploration based on explainable artificial intelligence approach.

    Global gene network exploration based on explainable artificial intelligence approach. oleh Heewon Park, Koji Maruhashi, Rui Yamaguchi, Seiya Imoto, Satoru Miyano

    Diterbitkan 2020-01-01
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  15. 15
    Correction: Global gene network exploration based on explainable artificial intelligence approach.

    Correction: Global gene network exploration based on explainable artificial intelligence approach. oleh Heewon Park, Koji Maruhashi, Rui Yamaguchi, Seiya Imoto, Satoru Miyano

    Diterbitkan 2021-01-01
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  16. 16
    Gene set-based module discovery decodes cis-regulatory codes governing diverse gene expression across human multiple tissues.

    Gene set-based module discovery decodes cis-regulatory codes governing diverse gene expression across human multiple tissues. oleh Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki, Satoru Miyano

    Diterbitkan 2010-06-01
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  17. 17
    Inference of gene regulatory networks incorporating multi-source biological knowledge via a state space model with L1 regularization.

    Inference of gene regulatory networks incorporating multi-source biological knowledge via a state space model with L1 regularization. oleh Takanori Hasegawa, Rui Yamaguchi, Masao Nagasaki, Satoru Miyano, Seiya Imoto

    Diterbitkan 2014-01-01
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  18. 18
    Prediction of transcriptional terminators in Bacillus subtilis and related species.

    Prediction of transcriptional terminators in Bacillus subtilis and related species. oleh Michiel J L de Hoon, Yuko Makita, Kenta Nakai, Satoru Miyano

    Diterbitkan 2005-08-01
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  19. 19
    Does Twitter trigger bursts in signature collections?

    Does Twitter trigger bursts in signature collections? oleh Rui Yamaguchi, Seiya Imoto, Masahiro Kami, Kenji Watanabe, Satoru Miyano, Koichiro Yuji

    Diterbitkan 2013-01-01
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  20. 20
    A unified simulation model for understanding the diversity of cancer evolution

    A unified simulation model for understanding the diversity of cancer evolution oleh Atsushi Niida, Takanori Hasegawa, Hideki Innan, Tatsuhiro Shibata, Koshi Mimori, Satoru Miyano

    Diterbitkan 2020-04-01
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