Research Summary

Selected Publications

• 1. Nakamura K, Kojima R, Uchino E, Ono K, Yanagita M, Murashita K, Itoh K, Nakaji S, Okuno Y:
  "Health improvement framework for actionable treatment planning using a surrogate Bayesian model"
  Nature Communications. 12:3088, 2021.
• 2. Matsumoto S, Ishida S, Araki M, Kato T, Terayama K, Okuno Y:
  "Extraction of protein dynamics information from cryo-EM maps using deep learning"
  Nature Machine Intelligence. 3:153-160, 2021.
• 3. Tanaka, Y, Higashihara, K, Nakazawa, M.A, Yamashita F, Tamada Y, Okuno Y
  "Dynamic changes in gene-to-gene regulatory networks in response to SARS-CoV-2 infection"
  Scientific Reports. 11:11241, 2021.
• 4. Kojima R, Ishida S, Ohta, M, Iwata H, Honma T, Okuno Y:
  "kGCN: a graph-based deep learning framework for chemical structure"
  Journal of Cheminformatics. 12:32, 2020.
• 5. Tanaka Y, Tamada Y, Ikeguchi M, Yamashita F, Okuno Y:
  "System-based differential gene network analysis for characterizing sample-specific subnetwork"
  Biomolecules. 10(2):306, 2020.
• 6. Tokuhisa, A, Kanada, R, Chiba, S, Terayama K, Isaka Y, Ma B, Kamiya N, Okuno Y
  "Coarse-grained diffraction template matching model to retrieve multiconformational models for biomolecule structures from noisy diffraction patterns"
  Journal of Chemical Information and Modeling. 60(6): 2803-2818, 2020.
• 7. Matsumoto S, Araki M, Isaka Y, Ono F, Hirohashi K, Ohashi S, Muto M, Okuno Y:
  "E487K-induced disorder in functionally relevant dynamics of mitochondrial aldehyde dehydrogenase 2"
  Biophysical Journal. 119(3):628-637, 2020.
• 8. Ishida S, Terayama K, Kojima R, Takasu K, Okuno Y:
  "Prediction and interpretable visualization of retrosynthetic reactions using graph convolutional networks"
  Journal of Chemical Information and Modeling. 59 (12):5026-5033, 2019.
• 9. Terayama K, Tamura R, Nose Y, Hiramatsu H, Hosono H, Okuno Y, Tsuda K:
  "Efficient construction method for phase diagrams using uncertainty sampling"
  Physical Review Materials. 3(3):033802, 2019.
• 10. Terayama K, Iwata H, Araki M, Okuno Y, Tsuda K:
  "Machine learning accelerates MD-based binding-pose prediction between ligands and proteins"
  Bioinformatics. 34(5):770-778, 2018.

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