Publications | Dr. Oleksandra Kukharenko

Shumaly, S.; Darvish, F.; Li, X.; Kukharenko, O.; Steffen, W.; Guo, Y.; Butt, H.-J.; Berger, R.: Estimating sliding drop width via side-view features using recurrent neural networks. Scientific Reports 14 (1), 12033 (2024)

Sawade, K.; Marx, A.; Peter, C.; Kukharenko, O.: Combining molecular dynamics simulations and scoring method to computationally model ubiquitylated linker histones in chromatosomes. PLoS Computational Biology 19 (8), e1010531 (2023)

Banerjee, A.; Hsu, H.-P.; Kremer, K.; Kukharenko, O.: Data-Driven Identification and Analysis of the Glass Transition in Polymer Melts. ACS Macro Letters 12 (6), pp. 679 - 684 (2023)

Hunkler, S.; Diederichs, K.; Kukharenko, O.; Peter, C.: Fast conformational clustering of extensive molecular dynamics simulation data. The Journal of Chemical Physics 158 (14), 144109 (2023)

Shumaly, S.; Darvish, F.; Li, X.; Saal, A.; Hinduja, C.; Steffen, W.; Kukharenko, O.; Butt, H.-J.; Berger, R.: Deep Learning to Analyze Sliding Drops. Langmuir 39 (3), pp. 1111 - 1122 (2023)

Banerjee, A.; Iscen, A.; Kremer, K.; Kukharenko, O.: Determining glass transition in all-atom acrylic polymeric melt simulations using machine learning. The Journal of Chemical Physics 159 (7), 074108 (2023)

Hunkler, S.; Buhl, T.; Kukharenko, O.; Peter, C.: Generating a conformational landscape of ubiquitin chains at atomistic resolution by back-mapping based sampling. Frontiers in Chemistry 10, 1087963 (2023)

Steuer, J.; Kukharenko, O.; Riedmiller, K.; Hartig, J. S.; Peter, C.: Guanidine-II aptamer conformations and ligand binding modes through the lens of molecular simulation. Nucleic Acids Research (London) 49 (14), pp. 7954 - 7965 (2021)

Dormann, D.; Fröhlich, R.; Dias, T.; Couto, N. B. d.; Heinss, N.; Hutten, S.; Küssner, K.; Ceron-Noriega, A.; Chargui, L.; Gelléri, M. et al.; Gopalan, A.; Hertäg, K.; Piccinno, R.; Rickert, C.; Schaaf, A.; Schumbera, E.; Shoup, S.; Stiehler, F.; Turunen, P.; Andrade-Navarro, M. A.; Beli, P.; Besenius, P.; Bonn, M.; Dahm, R.; Dhiman, S.; Gerber, S.; Girard, M.; Hülsmann, B.; Ketting, R.; Kim, E.; König, J.; Kremer, K.; Kukharenko, O.; Landfester, K.; Luck, K.; Methner, A.; Michels, J. J.; Möckel, M. M.; Morsbach, S.; Ritz, S.; Schick-Nickolaus, S.; Schmid, F.; Schmidt, C.; Schneider, D.; Schweiger, S.; Speck, T.; Stelzl, L.; Vrugt, M. t.; Ulrich, H. D.; Virnau, P.; Wachter, A.; Walther, A.; Weil, T.; Wittmann, S.; Lemke, E. A.: Polymers: The Hidden Heroes of Life. In: Science for a Better Tomorrow: Curious 2024 Insights, pp. 143 - 157 (Ed. Betz, U. A. K.). Springer, Cham (2025)

Shumaly, S.; Darvish, F.; Salehi, M.; Foumani, N. M.; Kukharenko, O.; Butt, H.-J.; Schwanecke, U.; Berger, R.: CNN-Transformer with Absolute Positional Encoding Optimized for Low-Dimensional Inputs: Applied to Estimate Sliding Drop Width. In: Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track: Lecture Notes in Computer Science, Vol. 16021, pp. 3 - 21. European Conference, ECML PKDD 2025, Porto, Portugal, September 15, 2025 - September 19, 2025. Springer Nature Switzerland, Cham (2026)