Yasuoka Laboratory


  • 2022年 (10 papers)
    • Kawada, R., Endo, K., Yasuoka, K., Kojima, H. and Matubayasi, N., "Prediction of Water Diffusion in Wide Varieties of Polymers with All-Atom Molecular Dynamics Simulations and Deep Generative Models", Journal of Chemical Information and Modeling, 63, 76-86(2022). (11 pages.) DOI: 10.1021/acs.jcim.2c01316

    • Kawada, R., Endo, K., Yuhara, D. and Yasuoka, K., "MD-GAN with multi-particle input: the machine learning of long-time molecular behavior from short-time MD data", Soft Matter, 18, 8446-8455(2022). (10 pages.) DOI: 10.1039/D2SM00852A

    • Kobayashi, Y., Arai, N. and Yasuoka, K., "Correlation between ordering and shear thinning in confined OMCTS liquids", The Journal of Chemical Physics, 157, 114506(2022). (10 pages.) DOI: 10.1063/5.0099473

    • Ishiyama, M., Yasuoka K. and Asai M., "Impact of free energy of polymers on polymorphism of polymer-grafted nanoparticles", Soft Matter, 18, 6318-6325(2022). (8 pages.) DOI: 10.1039/D2SM00311B

    • Kowaguchi, A., Endo, K., Brumby, P. E., Nomura, K. and Yasuoka, K., "Optimal Replica-Exchange Molecular Simulations in Combination with Evolution Strategies", Journal of Chemical Information and Modeling, 62, 6544-6552(2022). (9 pages.) DOI: 10.1021/acs.jcim.2c00608

    • Yasuda, I., Endo, K., Yamamoto, E., Hirano, Y., and Yasuoka, K., "Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein-ligand binding affinities", Communications Biology, 5, 481(2022). (9 pages.) DOI: 10.1038/s42003-022-03416-7

    • Peng, L., Arai, N., and Yasuoka, K., "A stochastic Hamiltonian formulation applied to dissipative particle dynamics", Applied Mathematics and Computation, 426, 127126(2022). (13 pages.) DOI: doi.org/10.1016/j.amc.2022.127126

    • Endo, K., Yuhara, D., and Yasuoka, K., "Efficient Monte Carlo Sampling for Molecular Systems Using Continuous Normalizing Flow", Journal of Chemical Theory and Computation, 18, 1395-1405(2022). (11 pages.) DOI: /10.1021/acs.jctc.1c01047

    • Suzuki, Y., Gao, Q., Pradel, K. C., Yasuoka, K., and Yamamoto, N., "Natural quantum reservoir computing for temporal information processing", Scientific Reports, 12, 1353(2022). (15 pages.) DOI: 10.1038/s41598-022-05061-w

    • Okada, K., Brumby, P. E. and Yasuoka, K., "An Efficient Random Number Generation Method for Molecular Simulation", Journal of Chemical Information and Modeling, 62, 71-78(2022). (8 pages.) DOI: 10.1021/acs.jcim.1c01206

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