Search results
Results: 36
Number of items: 36
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Rudzinski, J. F., Kloth, S., Wörner, S., Pal, T., Kremer, K., Bereau, T., & Vogel, M. (2021). Dynamical properties across different coarse-grained models for ionic liquids. Journal of Physics Condensed Matter, 33(22), Article 224001. https://doi.org/10.1088/1361-648X/abe6e1 -
Bereau, T. (2021). Computational compound screening of biomolecules and soft materials by molecular simulations. Modelling and Simulation in Materials Science and Engineering, 29(2), Article 023001. https://doi.org/10.1088/1361-651X/abd042
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Kleinwächter, I. S., Pannwitt, S., Centi, A., Hellmann, N., Thines, E., Bereau, T., & Schneider, D. (2021). The Bacteriostatic Activity of 2-Phenylethanol Derivatives Correlates with Membrane Binding Affinity. Membranes, 11(4), Article 254. https://doi.org/10.3390/membranes11040254
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Centi, A., Dutta, A., Parekh, S. H., & Bereau, T. (2020). Inserting Small Molecules across Membrane Mixtures: Insight from the Potential of Mean Force. Biophysical Journal, 118(6), 1321-1332. https://doi.org/10.1016/j.bpj.2020.01.039
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Girard, M., & Bereau, T. (2020). Regulating Lipid Composition Rationalizes Acyl Tail Saturation Homeostasis in Ectotherms. Biophysical Journal, 119(5), 892-899. https://doi.org/10.1016/j.bpj.2020.07.024
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Hoffmann, C., Centi, A., Menichetti, R., & Bereau, T. (2020). Molecular dynamics trajectories for 630 coarse-grained drug-membrane permeations. Scientific Data, 7, Article 51. https://doi.org/10.1038/s41597-020-0391-0
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Varolgünes, Y. B., Bereau, T., & Rudzinski, J. F. (2020). Interpretable embeddings from molecular simulations using Gaussian mixture variational autoencoders. Machine Learning: Science and Technology, 1(1), Article 015012. https://doi.org/10.1088/2632-2153/ab80b7
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Liu, C., Brandenburg, J. G., Valsson, O., Kremer, K., & Bereau, T. (2020). Free-energy landscape of polymer-crystal polymorphism. Soft Matter, 16(42), 9683-9692. https://doi.org/10.1039/d0sm01342k
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Scherer, C., Scheid, R., Andrienko, D., & Bereau, T. (2020). Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids. Journal of Chemical Theory and Computation, 16(5), 3194-3204. https://doi.org/10.1021/acs.jctc.9b01256
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