Publications 2020

  1. B

    1. T. Bauer, P. Buchholz, and J. Pleiss, “The modular structure of α/β-hydrolases.,” FEBS J, vol. 287, pp. 1035–1053, 2020.
  2. F

    1. M. Fischer, G. Bauer, and J. Gross, “Transferable Anisotropic United-Atom Mie (TAMie) Force Field: Transport Properties from Equilibrium Molecular Dynamic Simulations,” Industrial & Engineering Chemistry Research, vol. 59, no. 18, Art. no. 18, 2020.
    2. 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.
    3. 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.
  3. G

    1. 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.
    2. G. Gygli and J. Pleiss, “Simulation Foundry: automated and F.A.I.R. molecular modelling,” J Chem Inf Model, vol. 60, pp. 1922–1927, 2020.
  4. I

    1. 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.
  5. M

    1. M. M et al., “Diverse effects of aqueous polar co-solvents on Candida antarctica lipase B.,” Int J Biol Macromol, vol. 150, pp. 930–940, 2020.
    2. M. Mangiagalli et al., “Diverse effects of aqueous polar co-solvents on Candida antarctica lipase B.,” Int J Biol Macromol, vol. 150, pp. 930–940, 2020.
  6. N

    1. L. T. K. Nguyen, M. Rambausek, and M.-A. Keip, “Variational framework for distance-minimizing method in data-driven computational mechanics,” Computer Methods in Applied Mechanics and Engineering, vol. 365, p. 112898, 2020, doi: 10.1016/j.cma.2020.112898.
  7. S

    1. L. L. Schepp et al., “Digital rock physics and laboratory considerations on a high-porosity volcanic rock,” Scientific Reports, vol. 10, no. 1, Art. no. 1, 2020.
    2. L. L. Schepp et al., “Digital rock physics and laboratory considerations on a high-porosity volcanic rock: micro-XRCT data sets.” DaRUS, 2020, doi: 10.18419/DARUS-680.
    3. P. Stockinger, S. Roth, M. Müller, and J. Pleiss, “Systematic evaluation of imine-reducing enzymes: Common principles in imine reductases, β-hydroxyacid dehydrogenases, and short-chain dehydrogenases/reductases,” ChemBioChem, 2020.
    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 et al., “Stress-induced TRAILR2 expression overcomes TRAIL resistance in cancer cell spheroids,” Cell Death & Differentiation, pp. 1--16, 2020.
  8. V

    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, vol. 27, no. 8, Art. no. 8, 2020, doi: 10.1038/s41418-020-0512-5.
  9. W

    1. I. Wochner, D. Driess, H. Zimmermann, D. F. Haeufle, M. Toussaint, and S. Schmitt, “Optimality principles in human point-to-manifold reaching accounting for muscle dynamics,” Frontiers in Computational Neuroscience, vol. 14, p. 38, 2020.
To the top of the page