Andreas Raue
Andreas Raue
University of Augsburg
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Zitiert von
Zitiert von
Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood
A Raue, C Kreutz, T Maiwald, J Bachmann, M Schilling, U Klingmüller, ...
Bioinformatics 25 (15), 1923-1929, 2009
Lessons learned from quantitative dynamical modeling in systems biology
A Raue, M Schilling, J Bachmann, A Matteson, M Schelke, D Kaschek, ...
PloS one 8 (9), e74335, 2013
Analysis of single-cell RNA-seq identifies cell-cell communication associated with tumor characteristics
MP Kumar, J Du, G Lagoudas, Y Jiao, A Sawyer, DC Drummond, ...
Cell reports 25 (6), 1458-1468. e4, 2018
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
Estimation of immune cell content in tumour tissue using single-cell RNA-seq data
M Schelker, S Feau, J Du, N Ranu, E Klipp, G MacBeath, B Schoeberl, ...
Nature communications 8 (1), 2032, 2017
Comparison of approaches for parameter identifiability analysis of biological systems
A Raue, J Karlsson, MP Saccomani, M Jirstrand, J Timmer
Bioinformatics 30 (10), 1440-1448, 2014
Addressing parameter identifiability by model-based experimentation
A Raue, C Kreutz, T Maiwald, U Klingmüller, J Timmer
IET systems biology 5 (2), 120-130, 2011
Covering a broad dynamic range: information processing at the erythropoietin receptor
V Becker, M Schilling, J Bachmann, U Baumann, A Raue, T Maiwald, ...
Science 328 (5984), 1404-1408, 2010
Profile likelihood in systems biology
C Kreutz, A Raue, D Kaschek, J Timmer
The FEBS journal 280 (11), 2564-2571, 2013
Joining Forces of Bayesian and Frequentist Methodology: A Study for Inference in the Presence of Non-Identifiability
A Raue, C Kreutz, F Theis, J Timmer
Phil. Trans. Roy. Soc. A 371, 20110544, 2013
Identifiability and observability analysis for experimental design in nonlinear dynamical models
A Raue, V Becker, U Klingmüller, J Timmer
Chaos: An Interdisciplinary Journal of Nonlinear Science 20 (4), 2010
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
C Kreutz, A Raue, J Timmer
BMC Systems Biology 6, 120, 2012
Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range
J Bachmann, A Raue, M Schilling, ME Böhm, C Kreutz, D Kaschek, ...
Molecular systems biology 7 (1), 516, 2011
Driving the model to its limit: profile likelihood based model reduction
T Maiwald, H Hass, B Steiert, J Vanlier, R Engesser, A Raue, F Kipkeew, ...
PloS one 11 (9), e0162366, 2016
Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-cell lymphoma allows prediction of therapeutic targets
V Raia, M Schilling, M Böhm, B Hahn, A Kowarsch, A Raue, C Sticht, ...
Cancer research 71 (3), 693-704, 2011
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
Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach
P Meyer, T Cokelaer, D Chandran, KH Kim, PR Loh, G Tucker, M Lipson, ...
BMC systems biology 8, 1-18, 2014
Experimental design for parameter estimation of gene regulatory networks
B Steiert, A Raue, J Timmer, C Kreutz
PloS one 7 (7), e40052, 2012
Predictive mathematical models of cancer signalling pathways
J Bachmann, A Raue, M Schilling, V Becker, J Timmer, U Klingmüller
Journal of internal medicine 271 (2), 155-165, 2012
Bridging the gaps in systems biology
M Cvijovic, J Almquist, J Hagmar, S Hohmann, HM Kaltenbach, E Klipp, ...
Molecular Genetics and Genomics 289, 727-734, 2014
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