Publications of PN 2

  1. 2021

    1. A. Tomalka, S. Weidner, D. Hahn, W. Seiberl, and T. Siebert, “Power Amplification Increases With Contraction Velocity During Stretch-Shortening Cycles of Skinned Muscle Fibers,” Frontiers in Physiology, vol. 12, 2021, doi: 10.3389/fphys.2021.644981.
    2. M. Suditsch, P. Schröder, L. Lambers, T. Ricken, W. Ehlers, and A. Wagner, “Modelling basal-cell carcinoma behaviour in avascular skin,” PAMM, vol. 20, no. 1, Art. no. 1, 2021, doi: 10.1002/pamm.202000283.
    3. L. Lambers, M. Suditsch, A. Wagner, and T. Ricken, “A Multiscale and Multiphase Model of Function-Perfusion Growth Processes in the Human Liver,” PAMM, vol. 20, no. 1, Art. no. 1, 2021, doi: 10.1002/pamm.202000290.
    4. V. Klingel, J. Kirch, T. Ullrich, S. Weirich, A. Jeltsch, and N. E. Radde, “Model-based robustness and bistability analysis for methylation-based, epigenetic memory systems,” The FEBS Journal, 2021, doi: 10.1111/febs.15838.
    5. C. Boccellato et al., “Marizomib sensitizes primary glioma cells to apoptosis induced by a latest-generation TRAIL receptor agonist,” Cell Death & Disease, vol. 12, no. 7, Art. no. 7, 2021, doi: 10.1038/s41419-021-03927-x.
    6. F. Bertrand, L. Lambers, and T. Ricken, “Least Squares Finite Element Method for Hepatic Sinusoidal Blood Flow,” PAMM, vol. 20, no. 1, Art. no. 1, 2021, doi: 10.1002/pamm.202000306.

  2. 2020

    1. V. Vetma et al., “Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism,” Cell Death & Differentiation 2020, pp. 1--16, 2020, doi: 10.1038/s41418-020-0512-5.
    2. A. Tomalka, S. Weidner, D. Hahn, W. Seiberl, and T. Siebert, “Cross-Bridges and Sarcomeric Non-cross-bridge Structures Contribute to Increased Work in Stretch-Shortening Cycles,” Frontiers in Physiology, vol. 11, 2020, doi: 10.3389/fphys.2020.00921.
    3. D. Stöhr et al., “Stress-induced TRAILR2 expression overcomes TRAIL resistance in cancer cell spheroids,” Cell Death & Differentiation, 2020, doi: 10.1038/s41418-020-0559-3.
    4. D. Stöhr, A. Jeltsch, and M. Rehm, “TRAIL receptor signaling: From the basics of canonical signal transduction toward its entanglement with ER stress and the unfolded protein response.,” Cell Death Regulation in Health and Disease-Part A, p. 57, 2020.
    5. D. Stöhr and M. Rehm, “Linking hyperosmotic stress and apoptotic sensitivity,” The FEBS Journal, p. febs.15520, 2020, doi: 10.1111/febs.15520.
    6. D. Stöhr et al., “Stress-induced TRAILR2 expression overcomes TRAIL resistance in cancer cell spheroids,” Cell Death & Differentiation, pp. 1--16, 2020.
    7. K. Kuritz, D. Stöhr, D. S. Maichl, N. Pollak, M. Rehm, and F. Allgöwer, “Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities,” Scientific Reports, vol. 10, no. 1, Art. no. 1, 2020, doi: 10.1038/s41598-020-60400-z.
    8. D. Imig, N. Pollak, F. Allgöwer, and M. Rehm, “Sample-based modeling reveals bidirectional interplay between cell cycle progression and extrinsic apoptosis,” PLOS Computational Biology, vol. 16, no. 6, Art. no. 6, Jun. 2020, doi: 10.1371/journal.pcbi.1007812.
    9. C. Guttà et al., “Low expression of pro-apoptotic proteins Bax, Bak and Smac indicates prolonged progression-free survival in chemotherapy-treated metastatic melanoma,” Cell Death & Disease, vol. 11, no. 2, Art. no. 2, 2020, doi: 10.1038/s41419-020-2309-3.
    10. G. Fullstone, C. Guttà, A. Beyer, and M. Rehm, “The FLAME-accelerated signalling tool (FaST) for facile parallelisation of flexible agent-based models of cell signalling,” npj Systems Biology and Applications, vol. 6, no. 1, Art. no. 1, 2020, doi: 10.1038/s41540-020-0128-x.
    11. G. Fullstone, T. L. Bauer, C. Guttà, M. Salvucci, J. H. Prehn, and M. Rehm, “The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer,” Cell Death & Differentiation, pp. 1--15, 2020.
    12. G. Fullstone, T. L. Bauer, C. Guttà, M. Salvucci, J. H. M. Prehn, and M. Rehm, “The apoptosome molecular timer synergises with XIAP to suppress apoptosis execution and contributes to prognosticating survival in colorectal cancer,” Cell Death & Differentiation, 2020, doi: 10.1038/s41418-020-0545-9.

  3. 2019

    1. A. Tomalka, O. Röhrle, J.-C. Han, T. Pham, A. J. Taberner, and T. Siebert, “Extensive eccentric contractions in intact cardiac trabeculae: revealing compelling differences in contractile behaviour compared to skeletal muscles,” Proceedings of the Royal Society B, vol. 286, no. 1903, Art. no. 1903, 2019.
    2. T. Ricken and L. Lambers, “On computational approaches of liver lobule function and perfusion simulation,” GAMM-Mitteilungen, vol. 42, no. 4, Art. no. 4, 2019, doi: 10.1002/gamm.201900016.
    3. L. Lambers, T. Ricken, and M. König, “Model Order Reduction (MOR) of Function--Perfusion--Growth Simulation in the Human Fatty Liver via Artificial Neural Network (ANN),” PAMM, vol. 19, no. 1, Art. no. 1, 2019, doi: 10.1002/pamm.201900429.
    4. L. Lambers, T. Ricken, and M. König, “A multiscale and multiphase model for the description of function-perfusion processes in the human liver,” in Advances in Engineering Materials, Structures and Systems : Innovations, Mechanics and Applications : Proceedings of the 7th International Conference on Structural Engineering, Mechanics and Computation (SEMC 2019), September 2-4, 2019, Cape Town, South Africa, Cape Town, South Africa, 2019, pp. 304–307. doi: 10.1201/9780429426506-52.
    5. T. Kuhn, J. Dürrwächter, F. Meyer, A. Beck, C. Rohde, and C.-D. Munz, “Uncertainty quantification for direct aeroacoustic simulations of cavity flows,” J. Theor. Comput. Acoust., vol. 27, no. 1, 1850044, Art. no. 1, 1850044, 2019, doi: https://doi.org/10.1142/S2591728518500445.
    6. E.-M. Geissen, J. Hasenauer, and N. E. Radde, “Inference of finite mixture models and the effect of binning,” Statistical applications in genetics and molecular biology, vol. 18, no. 4, Art. no. 4, 2019.

  4. 2018

    1. T. Ricken, N. Waschinsky, and D. Werner, “Simulation of steatosis zonation in liver lobule—a continuummechanical bi-scale, tri-phasic, multi-component approach,” in Biomedical technology, Springer, 2018, pp. 15--33.
    2. D. Fink, A. Wagner, and W. Ehlers, “Application-driven model reduction for the simulation of therapeutic infusion processes in multi-component brain tissue,” JOURNAL OF COMPUTATIONAL SCIENCE, vol. 24, pp. 101–115, 2018, doi: 10.1016/j.jocs.2017.10.002.

  5. 2017

    1. P. Schröder, A. Wagner, D. Stöhr, M. Rehm, and W. Ehlers, “Variation of different growth descriptions in a metastatic proliferation model,” in Proceedings of the 7th GACM Colloquium on Computational Mechanics, M. von Scheven, M.-A. Keip, and N. Karajan, Eds. Stuttgart, 2017, pp. 259–262.
    2. S. Fechter, C.-D. Munz, C. Rohde, and C. Zeiler, “A sharp interface method for compressible liquid-vapor flow with phase    transition and surface tension,” JOURNAL OF COMPUTATIONAL PHYSICS, vol. 336, pp. 347–374, 2017, doi: 10.1016/j.jcp.2017.02.001.
    3. B. Christ et al., “Computational Modeling in Liver Surgery,” Frontiers in Physiology, vol. 8, p. 906, 2017, doi: 10.3389/fphys.2017.00906.

  6. 2016

    1. M. Redeker, C. Rohde, and I. S. Pop, “Upscaling of a tri-phase phase-field model for precipitation in porous    media,” IMA JOURNAL OF APPLIED MATHEMATICS, vol. 81, no. 5, Art. no. 5, 2016, doi: 10.1093/imamat/hxw023.

  7. 2015

    1. T. Ricken, D. Werner, H. G. Holzhütter, M. König, U. Dahmen, and O. Dirsch, “Modeling function--perfusion behavior in liver lobules including tissue, blood, glucose, lactate and glycogen by use of a coupled two-scale PDE--ODE approach,” Biomechanics and Modeling in Mechanobiology, vol. 14, no. 3, Art. no. 3, 2015, doi: 10.1007/s10237-014-0619-z.
    2. J. Neusser, C. Rohde, and V. Schleper, “Relaxation of the Navier-Stokes-Korteweg equations for compressible two-phase flow with phase transition,” International journal for numerical methods in fluids, vol. 79, no. 12, Art. no. 12, 2015, doi: 10.1002/fld.4065.
    3. F. Kissling and C. Rohde, “THE COMPUTATION OF NONCLASSICAL SHOCK WAVES IN POROUS MEDIA WITH A    HETEROGENEOUS MULTISCALE METHOD: THE MULTIDIMENSIONAL CASE,” MULTISCALE MODELING & SIMULATION, vol. 13, no. 4, Art. no. 4, 2015, doi: 10.1137/120899236.
    4. W. Ehlers and A. Wagner, “Multi-component modelling of human brain tissue: a contribution to the    constitutive and computational description of deformation, flow and    diffusion processes with application to the invasive drug-delivery    problem,” COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, vol. 18, no. 8, Art. no. 8, 2015, doi: 10.1080/10255842.2013.853754.

  8. 2013

    1. T. Ricken, U. Dahmen, O. Dirsch, and D. Q. Werner, “A Biphasic 3D-FEM model for the remodeling of microcirculation in liver lobes,” in Computer Models in Biomechanics, Springer, 2013, pp. 277--292.

  9. 2010

    1. T. Ricken, U. Dahmen, and O. Dirsch, “A biphasic model for sinusoidal liver perfusion remodeling after outflow obstruction,” Biomechanics and Modeling in Mechanobiology, vol. 9, no. 4, Art. no. 4, 2010, doi: 10.1007/s10237-009-0186-x.
    2. T. Ricken and J. Bluhm, “Remodeling and growth of living tissue: a multiphase theory,” Archive of Applied Mechanics, vol. 80, no. 5, Art. no. 5, 2010.

Project Network Coordinators

This picture showsNicole Radde
Prof. Dr. rer. nat.

Nicole Radde

[Photo: SimTech/Max Kovalenko]

This picture showsOliver Röhrle
Prof.

Oliver Röhrle

[Photo: SimTech/Max Kovalenko]

This picture showsSyn Schmitt
Prof. Dr. rer. nat.

Syn Schmitt

[Photo: SimTech/Max Kovalenko]

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