Publications funded or partly funded by Helmholtz-UQ.
- Albaraghtheh, T., Willumeit-Römer, R., Zeller-Plumhoff, B. (2022):
In silico studies of magnesium-based implants: A review of the current stage and challenges
Journal of Magnesium and Alloys
DOI: 10.1016/j.jma.2022.09.029 - AlBaraghtheh, T., Hermann, A., Shojaei, A., Willumeit-Römer, R., Cyron, C. J., & Zeller-Plumhoff, B. (2023):
Utilizing Computational Modelling to Bridge the Gap between In Vivo and In Vitro Degradation Rates for Mg-xGd Implants
Corrosion and Materials Degradation, 4(2), 274-283
DOI: 10.3390/cmd4020014 - Amrhein L, Fuchs C (2020):
Stochastic profiling of mRNA counts using HMC
In: Proceedings of the 35th International Workshop on Statistical Modelling (IWSM) 2020. - Amrhein L, Fuchs C (2021):
stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R
BMC Bioinformatics 22: 123.
DOI: 10.1186/s12859-021-03970-7 - Min, C., Yang, Q., Luo, H., Chen, D., Krumpen, T., Mamnun, N., … & Nerger, L. (2023).
Improving Arctic sea-ice thickness estimates with the assimilation of CryoSat-2 summer observations.
Ocean-Land-Atmosphere Research, 2, 0025.
DOI: 10.34133/olar.0025 - Contento L, Castelletti N, Raimúndez E, Le Gleut R, Schälte Y, Stapor P, Hinske LC, Hoelscher M, Wieser A, Radon K, Fuchs C, et al. (2021):
Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infection rates
medRxiv.
DOI: 10.1101/2021.10.01.21263052 - Cramer, E., Gorjão, L. R., Mitsos, A., Schäfer, B., Witthaut, D., & Dahmen, M. (2022).
Validation Methods for Energy Time Series Scenarios from Deep Generative Models.
IEEE Access, 10, 8194 - Fuetterer C, Augustin T, Fuchs C (2020):
Adapted single-cell consensus clustering (adaSC3)
Advances in Data Analysis and Classification volume 14(4): 885–896.
DOI: 10.1007/s11634-020-00428-1 - Gault, J. A., Freund, J. A., Hillebrand, H., & Gross, T. (2023).
Dissimilarity analysis based on diffusion maps.
Oikos, e10249. DOI:doi.org/10.1111/oik.10249 - S. Germscheid, M. Dahmen, A. Mitsos (2021).
Assessing the Demand Response Potential of Power-Intensive Processes by Stochastic Scheduling Optimization.
AIChE Annual Meeting, Nov 7-19, Boston, USA (2021) - Germscheid, S. H., Mitsos, A., & Dahmen, M. (2022)
Demand Response Potential of Industrial Processes Considering Uncertain Short‐term Electricity Prices.
AIChE Journal, e17828.
DOI:10.1002/aic.17828 - Gorjão, L. R., Jumar, R., Maass, H., Hagenmeyer, V., Yalcin, G. C., Kruse, J., Timme, M., Beck, C., Witthaut, D., & Schäfer, B. (2020).
Open database analysis of scaling and spatio-temporal properties of power grid frequencies.
Nature communications, 11(1), 6362. - Gorjão, L. R., Schäfer, B., Witthaut, D., & Beck, C. (2021).
Spatio-temporal complexity of power-grid frequency fluctuations.
New Journal of Physics, 23, 073016. - Gorjão, L. R., Witthaut, D., Lehnertz, K., & Lind, P. G. (2021).
Arbitrary-Order Finite-Time Corrections for the Kramers–Moyal Operator.
Entropy, 23(5), 517. - Gorjão, L. R., Hassan, G., Kurths, J., & Witthaut, D. (2022).
MFDFA: Efficient Multifractal Detrended Fluctuation Analysis in Python.
Computer Physics Communications, 273, 108254. - Gorjão, L. R., Vanfretti, L., Witthaut, D., Beck, C., & Schäfer, B. (2021).
Phase and amplitude synchronisation in power-grid frequency fluctuations in the Nordic Grid.
IEEE Access, 10, 18065–18073. - Graham, Jasmin, Angelos Hannides, Nabir Mamnun, Lina E. Sitz, Ian D. Walsh, Elisha M. Wood-Charlson, and Leandro Ponsoni.
“Ocean Sciences Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science.”
Earth and Space Science 9 (2022), e2021EA002124.
DOI: 10.1029/2021EA002124 - Han, C., Hilger, H., Mix, E., Böttcher, P., Reyers, M., Beck, C., Witthaut, D., & Gorjão, L. R. (2022).
Complexity and persistence of price time series of the European electricity spot market.
PRX Energy, 1(1), 013002. - A. Jozi Najafabadi, Ch. Haberland, T. Ryberg, V. Verwater, E. Le Breton, M. R. Handy, M. Weber, and the AlpArray working group (2021):
Relocation of earthquakes in the Southern and Eastern Alps (Austria, Italy) recorded by the dense, temporary SWATH–D network using a Markov chain Monte Carlo inversion.
Solid Earth, 12, 5, 1087-1109.
DOI: 10.5194/se-12-1087-2021 - Jumar, R., Maaß, H., Schäfer, B., Gorjão, L. R., & Hagenmeyer, V. (2020).
Power grid frequency data base.
arXiv preprint arXiv:2006.01771. - Mamnun, Nabir, Christoph Völker, Mihalis Vrekoussis, and Lars Nerger (2022).
Uncertainties in Ocean Biogeochemical Simulations: Application of Ensemble Data Assimilation to a One-Dimensional Model.
Original Research, Frontiers in Marine Science 9.
DOI: 10.3389/fmars.2022.984236 - Mamnun, N., Völker, C., Krumscheid, S., Vrekoussis, M., & Nerger, L. (2023).
Global sensitivity analysis of a one-dimensional ocean biogeochemical model.
Socio-Environmental Systems Modelling, 5, 18613.
DOI: 10.18174/sesmo.18613 - Olbrich L, Castelletti N, Schälte Y, Garí M, Pütz P, Bakuli A, Pritsch M, Kroidl I, Saathoff E, Noller JMG, Fingerle V, Fuchs C, et al. (2021):
A Serology Strategy for Epidemiological Studies Based on the Comparison of the Performance of Seven Different Test Systems - The Representative COVID-19 Cohort Munich
bioRxiv.
DOI: 10.1101/2021.01.13.21249735 - Olbrich L, Castelletti N, Schälte Y, Garí M, Pütz P, Bakuli A, Pritsch M, Kroidl I, Saathoff E, Guggenbuehl Noller J, Fingerle V, Fuchs C, et al. (2021):
Head-to-head evaluation of seven different seroassays including direct viral neutralisation in a representative cohort for SARS-CoV-2
Journal of General Virology 102(10).
DOI: 10.1099/jgv.0.001653 - Paasche, H., Paasche, K., Dietrich, P., (2020):
Uncertainty as a driving force for geoscientific development
Nat. Cult. 15 (1), 1 - 18
DOI: 10.3167/nc.2020.150101 - Paasche, H., Gross, M., Lüttgau, J., Greenberg, D.S., Weigel, T., (2021):
To the brave scientists: Aren’t we strong enough to stand (and profit from) uncertainty in Earth system measurement and modelling?
Geosci. Data J.
DOI: 10.1002/gdj3.132 - Pieschner S, Fuchs C (2020):
Bayesian inference for diffusion processes: using higher-order approximations for transition densities
Royal Society Open Science 7(10): 200270.
DOI: 10.1098/rsos.200270 - Pieschner S, Hasenauer J, Fuchs C (2021):
Identifiability analysis for models of the translation kinetics after mRNA transfection
bioRxiv (accepted by Journal of Mathematical Biology).
DOI: 10.1101/2021.05.18.444633 - Pritsch M, Radon K, Bakuli A, Le Gleut R, Olbrich L, Guggenbuehl Noller JM, Saathoff E, Castelletti N, Garí M, Pütz P, Schaelte Y, Fuchs C, et al. (2021):
Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich
International journal of environmental research and public health 18(7): 3572.
DOI: 10.2139/ssrn.3745128 - Radon K, Bakuli A, Pütz P, Gleut RL, Guggenbuehl Noller JM, Olbrich L, Saathoff E, Garí M, Schälte Y, Frahnow T, Wölfel R, Fuchs C, et al. (2021):
From first to second wave: follow-up of the prospective Covid-19 cohort (KoCo19) in Munich (Germany)
BMC infectious diseases 21(1): 925.
DOI: 10.1186/s12879-021-06589-4 - Tilmann, F., Sadeghisorkhani, H., Mauerberger, A. (2020):
Another look at the treatment of data uncertainty in Markov chain Monte Carlo inversion and other probabilistic methods.
Geophysical Journal International, 222, 1, 388-405.
DOI: 10.1093/gji/ggaa168 - B. Zeller-Plumhoff*ǂ, T. AlBaraghthehǂ, D. Höche, R. Willumeit-Römer
Computational modelling of magnesium degradation in simulated body fluid under physiological conditions
accepted at Magnesium and Alloys
ǂ shared first authorship - Zöller, G., Hainzl, S., Tilmann, F., Woith, H., Dahm, T. (2021):
Comment on “Potential short‐term earthquake forecasting by farm animal monitoring” by Wikelski, Mueller, Scocco, Catorci, Desinov, Belyaev, Keim, Pohlmeier, Fechteler, and Mai.
Ethology, 127, 3, 302-306.
DOI: 10.1111/eth.13105