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1.
Kapfer, E.M.* ; Stapor, P. & Hasenauer, J.: Challenges in the calibration of large-scale ordinary differential equation models. IFAC PapersOnline 52, 58-64 (2019)
2.
Lines, G.T.* et al.: Efficient computation of steady states in large-scale ODE models of biochemical reaction networks. IFAC PapersOnline 52, 32-37 (2019)
3.
Villaverde, A.F.* ; Raimundez-Alvarez, E. ; Hasenauer, J. & Banga, J.R.*: A comparison of methods for quantifying prediction uncertainty in systems biology. IFAC PapersOnline 52, 45-51 (2019)
4.
Wang, D. ; Stapor, P. & Hasenauer, J.: Dirac mixture distributions for the approximation of mixed effects models. IFAC PapersOnline 52, 200-206 (2019)
5.
Schälte, Y. ; Stapor, P. & Hasenauer, J.: Evaluation of derivative-free optimizers for parameter estimation in systems biology. IFAC PapersOnline 51, 98-101 (2018)
6.
Hross, S. ; Fiedler, A. ; Theis, F.J. & Hasenauer, J.: Quantitative comparison of competing PDE models for Pomlp dynamics in fission yeast. In: (Foundations of Systems Biology in Engineering - FOSBE 2016, 9—12 October 2016, Magdeburg). 2016. 264-269 (IFAC PapersOnline ; 49-26)
7.
Kazeroonian, A. ; Theis, F.J. & Hasenauer, J.: Modeling of stochastic biological processes with non-polynomial propensities using non-central conditional moment equation. IFAC PapersOnline 19, 1729-1735 (2014)
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