Jan Hasenauer
TitleCited byYear
Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems
A Raue, B Steiert, M Schelker, C Kreutz, T Maiwald, H Hass, J Vanlier, ...
Bioinformatics 31 (21), 3558-3560, 2015
Method of conditional moments (MCM) for the chemical master equation
J Hasenauer, V Wolf, A Kazeroonian, FJ Theis
Journal of mathematical biology 69 (3), 687-735, 2014
Identification of models of heterogeneous cell populations from population snapshot data
J Hasenauer, S Waldherr, M Doszczak, N Radde, P Scheurich, F Allgöwer
BMC bioinformatics 12 (1), 125, 2011
Determinants of robustness in spindle assembly checkpoint signalling
S Heinrich, EM Geissen, J Kamenz, S Trautmann, C Widmer, P Drewe, ...
Nature cell biology 15 (11), 1328, 2013
Network plasticity of pluripotency transcription factors in embryonic stem cells
A Filipczyk, C Marr, S Hastreiter, J Feigelman, M Schwarzfischer, ...
Nature cell biology 17 (10), 1235, 2015
Characterization of rare, dormant, and therapy-resistant cells in acute lymphoblastic leukemia
S Ebinger, EZ Özdemir, C Ziegenhain, S Tiedt, CC Alves, M Grunert, ...
Cancer cell 30 (6), 849-862, 2016
High-dimensional Bayesian parameter estimation: Case study for a model of JAK2/STAT5 signaling
S Hug, A Raue, J Hasenauer, J Bachmann, U Klingmüller, J Timmer, ...
Mathematical Biosciences 246 (2), 293-304, 2013
Inference for stochastic chemical kinetics using moment equations and system size expansion
F Fröhlich, P Thomas, A Kazeroonian, FJ Theis, R Grima, J Hasenauer
PLoS computational biology 12 (7), e1005030, 2016
Parameter identification, experimental design and model falsification for biological network models using semidefinite programming
J Hasenauer, S Waldherr, K Wagner, F Allgöwer
IET systems biology 4 (2), 119-130, 2010
Scalable parameter estimation for genome-scale biochemical reaction networks
F Fröhlich, B Kaltenbacher, FJ Theis, J Hasenauer
PLoS computational biology 13 (1), e1005331, 2017
ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics
J Hasenauer, C Hasenauer, T Hucho, FJ Theis
PLoS computational biology 10 (7), e1003686, 2014
Analysis and simulation of division-and label-structured population models
J Hasenauer, D Schittler, F Allgöwer
Bulletin of mathematical biology 74 (11), 2692-2732, 2012
Dominant negative effects of tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) receptor 4 on TRAIL receptor 1 signaling by formation of heteromeric complexes
S Neumann, J Hasenauer, N Pollak, P Scheurich
Journal of Biological Chemistry 289 (23), 16576-16587, 2014
Wound-healing growth factor, basic FGF, induces Erk1/2-dependent mechanical hyperalgesia
C Andres, J Hasenauer, HS Ahn, EK Joseph, J Isensee, FJ Theis, ...
PAIN® 154 (10), 2216-2226, 2013
Pain modulators regulate the dynamics of PKA-RII phosphorylation in subgroups of sensory neurons
J Isensee, M Diskar, S Waldherr, R Buschow, J Hasenauer, A Prinz, ...
J Cell Sci 127 (1), 216-229, 2014
CERENA: ChEmical REaction Network Analyzer—a toolbox for the simulation and analysis of stochastic chemical kinetics
A Kazeroonian, F Fröhlich, A Raue, FJ Theis, J Hasenauer
PloS one 11 (1), e0146732, 2016
PESTO: parameter estimation toolbox
P Stapor, D Weindl, B Ballnus, S Hug, C Loos, A Fiedler, S Krause, ...
Bioinformatics 34 (4), 705-707, 2017
Cell differentiation modeled via a coupled two-switch regulatory network
D Schittler, J Hasenauer, F Allgöwer, S Waldherr
Chaos: An Interdisciplinary Journal of Nonlinear Science 20 (4), 045121, 2010
A generalized population model for cell proliferation: Integrating division numbers and label dynamics
D Schittler, J Hasenauer, F Allgöwer
TICSP series 57, 165-168, 2011
Parallelization and high-performance computing enables automated statistical inference of multi-scale models
N Jagiella, D Rickert, FJ Theis, J Hasenauer
Cell systems 4 (2), 194-206. e9, 2017
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Articles 1–20