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21.
Lordick, F.* et al.: Heterogeneity of HER2 expression in gastric cancer (GC) leads to high deviation rates between local and central testing and hampers efficacy of anti-HER2 therapy: Survival results from the VARIANZ study. Cancer Res. 78 (2018)
22.
Schälte, Y. ; Stapor, P. & Hasenauer, J.: Evaluation of derivative-free optimizers for parameter estimation in systems biology. IFAC PapersOnline 51, 98-101 (2018)
23.
Stapor, P. et al.: PESTO: Parameter EStimation TOolbox. Bioinformatics 34, 705-707 (2018)
24.
Stapor, P. ; Fröhlich, F. & Hasenauer, J.: Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis. Bioinformatics 34, 151-159 (2018)
25.
Wierling, C.* et al.: CanPathPro-development of a platform for predictive pathway modelling using genetically engineered mouse models. Cancer Res. 78 (2018)
26.
Ballnus, B. et al.: Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems. BMC Syst. Biol. 11:63 (2017)
27.
Fröhlich, F. ; Theis, F.J. ; Rädler, J.O.* & Hasenauer, J.: Parameter estimation for dynamical systems with discrete events and logical operations. Bioinformatics 33, 1049-1056 (2017)
28.
Fröhlich, F. ; Kaltenbacher, B.* ; Theis, F.J. & Hasenauer, J.: Scalable parameter estimation for genome-scale biochemical reaction networks. PLoS Comput. Biol. 13:e1005331 (2017)
29.
Jagiella, N. ; Rickert, D. ; Theis, F.J. & Hasenauer, J.: Parallelization and high-performance computing enables automated statistical inference of multi-scale models. Cell Syst. 4, 194–206.e9 (2017)
30.
Kazeroonian, A. ; Theis, F.J. & Hasenauer, J.: A scalable moment-closure approximation for large-scale biochemical reaction networks. Bioinformatics 33, i293-i300 (2017)
31.
Keller, S.* et al.: Evaluation of epidermal growth factor receptor signaling effects in gastric cancer cell lines by detailed motility-focused phenotypic characterization linked with molecular analysis. BMC Cancer 17:845 (2017)
32.
Klinger, E. & Hasenauer, J.: A scheme for adaptive selection of population sizes in approximate Bayesian Computation - Sequential Monte Carlo. Lecture Notes Comp. Sci. 10545 LNBI, 128-144 (2017)
33.
Ligon, T.S.* et al.: GenSSI 2.0: Multi-experiment structural identifiability analysis of SBML models. Bioinformatics 34, 1421-1423 (2017)
34.
Maier, C. ; Loos, C. & Hasenauer, J.: Robust parameter estimation for dynamical systems from outlier-corrupted data. Bioinformatics 33, 1-8 (2017)
35.
Blasi, T. et al.: Combinatorial histone acetylation patterns are generated by motif-specific reactions. Cell Syst. 2, 49-58 (2016)
36.
Boiger, R.* ; Hasenauer, J. ; Hross, S. & Kaltenbacher, B.*: Integration based profile likelihood calculation for PDE constrained parameter estimation problems. Inverse Probl. 32:125009 (2016)
37.
Ebinger, S. et al.: Characterization of rare, dormant, and therapy-resistant cells in acute lymphoblastic leukemia. Cancer Cell 30, 849-862 (2016)
38.
Fiedler, A. ; Raeth, S.* ; Theis, F.J. ; Hausser, A.* & Hasenauer, J.: Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints. BMC Syst. Biol. 10:80 (2016)
39.
Fröhlich, F. et al.: Inference for stochastic chemical kinetics using moment equations and system size expansion. PLoS Comput. Biol. 12:e1005030 (2016)
40.
Fröhlich, F. et al.: Large-scale modeling of cancer signaling: Mechanistic modeling meets Big Data. Eur. J. Cancer 68, S44-S44 (2016)