CitingProjects

Biological projects conducted with Data2Dynamics

[1] J. Bachmann, A. Raue, M. Schilling, M. B�ohm, C. Kreutz, D. Kaschek, H. Busch, N. Gretz, W. Lehmann, J. Timmer, and U. Klingm�uller. Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Molecular Systems Biology, 7:516, 2011.

[2] B. Steiert, A. Raue, J. Timmer, and C. Kreutz. Experimental design for parameter estimation of gene regulatory networks. PLoS ONE, 7(7):e40052, 2012.

[3] E. Gin, A. C. R. Diernfellner, M. Brunner, and T. H�ofer. The Neurospora photoreceptor VIVID exerts negative and positive control on light sensing to achieve adaptation. Molecular Systems Biology, 9(667):667, 2013.

[4] K. M�uller, R. Engesser, S. Metzger, S. Schulz, M. M. K�ampf, M. Busacker, T. Steinberg, P. Tomakidi, M. Ehrbar, F. Nagy, J. Timmer, M. D. Zubriggen, and W.Weber. A red/far-red light-responsive bi-stable toggle switch to control gene expression in mammalian cells. Nucleic Acids Research, 41(7):e77, 2013.

[5] K. M�uller, R. Engesser, S. Schulz, T. Steinberg, P. Tomakidi, C. C. Weber, R. Ulm, J. Timmer, M. D. Zurbriggen, and W. Weber. Multi-chromatic control of mammalian gene expression and signaling. Nucleic Acids Research, 41(12):e124, 2013.

[6] K. M�uller, R. Engesser, J. Timmer, F. Nagy, M. D. Zurbriggen, and W. Weber. Synthesis of phycocyanobilin in mammalian cells. Chemical Communications, 49(79):8970-8972, 2013.

[7] R. Beer, K. Herbst, N. Ignatiadis, I. Kats, L. Adlung, H. Meyer, D. Niopek, T. Christiansen, F. Georgi, N. Kurzawa, J. Meichsner, S. Rabe, A. Riedel, J. Sachs, J. Schessner, F. Schmidt, P. Walch, K. Niopek, T. Heinemann, R. Eils, and B. Di Ventura. Creating functional engineered variants of the single-module nonribosomal peptide synthetase IndC by T domain exchange. Molecular bioSystems, 10(7):1709-18, 2014.

[8] M. E. Boehm, L. Adlung, M. Schilling, S. Roth, U. Klingm�uller, and W. D. Lehmann. Identication of isoform-specic dynamics in phosphorylation-dependent STAT5 dimerization by quantitative mass spectrometry and mathematical modeling. Journal of Proteome Research, 13(12):5685-94, 2014.

[9] J. Kanodia, D. Chai, J. Vollmer, J. Kim, A. Raue, G. Finn, and B. Schoeberl. Deciphering the mechanism behind broblast growth factor (FGF) induced biphasic signal-response proles. Cell Communication and Signaling, 12:34, 2014.

[10] P. Meyer, T. Cokelaer, D. Chandran, K. H. Kim, P.-R. Loh, G. Tucker, M. Lipson, B. Berger, C. Kreutz, A. Raue, et al. Network topology and parameter estimation: From experimental design methods to gene regulatory network kinetics using a community based approach. BMC Systems Biology, 8(1):13, 2014.

[11] K. M�uller, R. Engesser, J. Timmer, M. D. Zurbriggen, and W. Weber. Orthogonal optogenetic triple-gene control in Mammalian cells. ACS Synthetic Biology, 3(11):796-801, 2014.

[12] P. Verbruggen, T. Heinemann, E. Manders, G. von Bornstaedt, R. van Driel, and T. H�ofer. Robustness of DNA repair through collective rate control. PLoS Compu- tational Biology, 10(1):e1003438, 2014.

[13] L. A. D'Alessandro, R. Samaga, T. Maiwald, S.-H. Rho, S. Bonefas, A. Raue, N. Iwamoto, A. Kienast, K. Waldow, R. Meyer, et al. Disentangling the complexity of hgf signaling by combining qualitative and quantitative modeling. PLoS compu- tational biology, 11(4):e1004192, 2015.

[14] Y. Guan, M. Meurer, S. Raghavan, A. Rebane, J. R. Lindquist, S. Santos, I. Kats, M. W. Davidson, R. Mazitschek, T. E. Hughes, et al. Live-cell multiphoton uorescence correlation spectroscopy with an improved large Stokes shift uorescent protein. Molecular Biology of the Cell, 26(11):2054-2066, 2015.

[15] H. Klett, M. Rodriguez-Fernandez, S. Dineen, L. R. Leon, J. Timmer, and F. J. Doyle. Modeling the in ammatory response in the hypothalamus ensuing heat stroke: Iterative cycle of model calibration, identiability analysis, experimental design and data collection. Mathematical Biosciences, 260:35-46, 2015.

[16] N. Mende, E. E. Kuchen, M. Lesche, T. Grinenko, K. D. Kokkaliaris, H. Hanenberg, D. Lindemann, A. Dahl, A. Platz, T. H�ofer, et al. CCND1-CDK4-mediated cell cycle progression provides a competitive advantage for human hematopoietic stem cells in vivo. Journal of Experimental Medicine, page 20150308, 2015.

[17] Y. Murakawa, M. Hinz, J. Mothes, A. Schuetz, M. Uhl, E. Wyler, T. Yasuda, G. Mastrobuoni, C. C. Friedel, L. D�olken, et al. RC3H1 post-transcriptionally regulates A20 mRNA and modulates the activity of the IKK/NF-B pathway. Nature Communications, 6:7367, 2015.

[18] N. Iwamoto, L. A. D'Alessandro, S. Depner, B. Hahn, B. A. Kramer, P. Lucarelli, A. Vlasov, M. Stepath, M. E. B�ohm, D. Deharde, et al. Context-specic ow through the MEK/ERK module produces cell-and ligand-specic patterns of ERK single and double phosphorylation. Science Signaling, 9(413):ra13, 2016.

[19] R. Merkle, B. Steiert, F. Salopiata, S. Depner, A. Raue, N. Iwamoto, M. Schelker, H. Hass, M. W�asch, M. E. B�ohm, et al. Identication of cell type-specic dierences in erythropoietin receptor signaling in primary erythroid and lung cancer cells. PLoS Computational Biology, 12(8):e1005049, 2016.

[20] M. Schelker, C. M. Mair, F. Jolmes, R.-W. Welke, E. Klipp, A. Herrmann, M. Fl�ottmann, and C. Sieben. Viral RNA degradation and diusion act as a bottleneck for the influenza A virus infection eciency. PLoS Computational Biology, 12(10):e1005075, 2016.

[21] L. Adlung, S. Kar, M.-C. Wagner, B. She, S. Chakraborty, J. Bao, S. Lattermann, M. Boerries, H. Busch, P. Wuchter, et al. Protein abundance of AKT and ERK pathway components governs cell type-specic regulation of proliferation. Molecular Systems Biology, 13(1):904, 2017.

[22] R. Borowiak, W. Reichardt, D. Kurzhunov, C. Schuch, J. Leupold, A. J. Krat, M. Reisert, T. Lange, E. Fischer, and M. Bock. Initial investigation of glucose metabolism in mouse brain using enriched 17O-glucose and dynamic 17O-MRS. NMR in Biomedicine, 30(8), 2017.

[23] P. Dutta, V. Devaraj, and B. Bose. A negative feedback regulates the ow of signal through akt/mtorc1/s6k1 pathway. bioRxiv, page 147710, 2017.

[24] H. Hass, F. Kipkeew, A. Gauhar, E. Bouche, P. May, J. Timmer, and H. H. Bock. Mathematical model of early Reelin-induced Src family kinase-mediated signaling. PLoS ONE, 12(10):e0186927, 2017.

[25] H. Hass, K. Masson, S. Wohlgemuth, V. Paragas, J. E. Allen, M. Sevecka, E. Pace, J. Timmer, J. Stelling, G. MacBeath, et al. Predicting ligand-dependent tumors from multi-dimensional signaling features. NPJ Systems Biology and Applications, 3(1):27, 2017.

[26] A. Kulawik, R. Engesser, C. Ehlting, A. Raue, U. Albrecht, B. Hahn, W.-D. Lehmann, M. Gaestel, U. Klingm�uller, D. H�aussinger, et al. IL-1-induced and p38MAPK-dependent activation of the mitogen-activated protein kinase-activated protein kinase 2 (MK2) in hepatocytes: Signal transduction with robust and concentration-independent signal amplication. Journal of Biological Chemistry, 292(15):6291-6302, 2017.

[27] D. Kurzhunov, R. Borowiak, H. Hass, P. Wagner, A. J. Krat, J. Timmer, and M. Bock. Quantication of oxygen metabolic rates in Human brain with dynamic 17O MRI: Prole likelihood analysis. Magnetic Resonance in Medicine, 78(3):1157- 1167, 2017.

[28] D. Kurzhunov, R. Borowiak, M. Reisert, A. J. Krat, A. C. � Ozen, and M. Bock. 3D CMRO2 mapping in human brain with direct 17O MRI: Comparison of conventional and proton-constrained reconstructions. Neuroimage, 155:612-624, 2017.

[29] T. Ryl, E. E. Kuchen, E. Bell, C. Shao, A. F. Florez, G. M�onke, S. Gogolin, M. Friedrich, F. Lamprecht, F. Westermann, et al. Cell-cycle position of single MYC-driven cancer cells dictates their susceptibility to a chemotherapeutic drug. Cell Systems, 5(3):237-250, 2017.

[30] S. Sobotta, A. Raue, X. Huang, J. Vanlier, A. J�unger, S. Bohl, U. Albrecht, M. J. Hahnel, S. Wolf, N. S. Mueller, et al. Model based targeting of IL-6-Induced in- ammatory responses in cultured primary hepatocytes to improve application of the JAK inhibitor ruxolitinib. Frontiers in Physiology, 8:775, 2017.

[31] S. Vullo, G. Bonifacio, S. Roy, N. Johner, S. Berneche, and S. Kellenberger. Conformational dynamics and role of the acidic pocket in ASIC pH-dependent gating. Proceedings of the National Academy of Sciences, 114(14):201620560, 2017.

[32] D. Zander, D. Samaga, R. Straube, and K. Bettenbrock. Bistability and nonmonotonic induction of the lac operon in the natural lactose uptake system. Biophysical Journal, 112(9):1984-1996, 2017.

[33] C. T�önsing, J. Timmer, and C. Kreutz. Prole likelihood-based analyses of infectious disease models. Statistical Methods in Medical Res., OnlineFirst/in press, 2018.

[34] H. M. Beyer, R. Engesser, M. H�orner, J. Koschmieder, P. Beyer, J. Timmer, M. D. Zurbriggen, and W. Weber. Synthetic biology makes polymer materials count. Advanced Materials, 1800472, 2018.

[35] C. Li, F. Cesbron, M. Oehler, M. Brunner, and T. H�ofer. Frequency modulation of transcriptional bursting enables sensitive and rapid gene regulation. Cell Systems, 2018, in press.

[36] P. Lucarelli, M. Schilling, C. Kreutz, A. Vlasov, M. E. Boehm, N. Iwamoto, B. Steiert, S. Lattermann, M. Wasch, M. Stepath, M. S. Matter, M. Heikenwalder, K. Homann, D. Deharde, G. Damm, D. Seehofer, M. Muciek, N. Gretz, W. D. Lehmann, J. Timmer, and U. Klingmuller. Resolving the combinatorial complexity of Smad protein complex formation and its link to gene expression. Cell Systems, 6(1):75-89, 2018.

[37] J. Strasen, U. Sarma, M. Jentsch, S. Bohn, C. Sheng, D. Horbelt, P. Knaus, S. Legewie, and A. Loewer. Cell-specic responses to the cytokine TGF are determined by variability in protein levels. Molecular Systems Biology, 14(1):e7733, 2018.

[38] K. Tummler, M. Zimmermann, O. T. Schubert, R. Aebersold, C. K�uhn, U. Sauer, and E. Klipp. Two parallel pathways implement robust propionate catabolism and detoxication in mycobacteria. bioRxiv, page 258947, 2018.

Methodological studies and enhancements of Data2Dynamics

[1] A. Raue, V. Becker, U. Klingm�uller, and J. Timmer. Identiability and observability analysis for experimental design in non-linear dynamical models. Chaos, 20(4):045105, 2010.

[2] A. Raue, C. Kreutz, T. Maiwald, U. Klingm�uller, and J. Timmer. Addressing parameter identiability by model-based experimentation. IET Systems Biology, 5(2):120-130, 2011.

[3] C. Kreutz, A. Raue, and J. Timmer. Likelihood based observability analysis and condence intervals for predictions of dynamic models. BMC Systems Biology, 6:120, 2012.

[4] M. Schelker, A. Raue, J. Timmer, and C. Kreutz. Comprehensive estimation of input signals and dynamical parameters in biochemical reaction networks. Bioin- formatics, 28(18):i522-i528, 2012.

[5] S. Hug, A. Raue, J. Hasenauer, J. Bachmann, U. Klingm�uller, J. Timmer, and F. Theis. High-dimensional Bayesian parameter estimation: Case study for a model of JAK2/STAT5 signaling. Mathematical Biosciences, 246(2):293-304, 2013.

[6] C. Kreutz, A. Raue, D. Kaschek, and J. Timmer. Prole likelihood in systems biology. FEBS Journal, 280(11):2564-2571, 2013.

[7] A. Raue, M. Schilling, J. Bachmann, A. Matteson, M. Schelker, D. Kaschek, S. Hug, C. Kreutz, B. Harms, F. Theis, U. Klingm�uller, and J. Timmer. Lessons learned from quantitative dynamical modeling in systems biology. PLoS ONE, 8(9):e74335, 2013.

[8] A. Raue, C. Kreutz, F. Theis, and J. Timmer. Joining forces of Bayesian and frequentist methodology: A study for inference in the presence of non-identiability. Philosophical Transactions of the Royal Society A, 371:20110544, 2013.

[9] A. Raue, J. Karlsson, M. Saccomani, M. Jirstrand, and J. Timmer. Comparison of approaches for parameter identiability analysis of biological systems. Bioinfor- matics, 30(10):1440-1448, 2014.

[10] C. Tönsing, J. Timmer, and C. Kreutz. Cause and cure of sloppiness in ordinary differential equation models. Physical Review E, 90:023303, 2014.

[11] H. Hass, C. Kreutz, J. Timmer, and D. Kaschek. Fast integration-based prediction bands for ordinary differential equation models. Bioinformatics, 32(8):1204-1210, 2015.

[12] C. Kreutz, A. Raue, and J. Timmer. Statistics for model calibration. In Multiple Shooting and Time Domain Decomposition Methods, pages 355-375. Springer, 2015.

[13] A. Raue, B. Steiert, M. Schelker, C. Kreutz, T. Maiwald, H. Hass, J. Vanlier, C. T�onsing, L. Adlung, R. Engesser, W. Mader, T. Heinemann, J. Hasenauer, M. Schilling, T. H�ofer, E. Klipp, F. Theis, U. Klingm�uller, B. Schoeberl, and J. Timmer. Data2Dynamics: A modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics, 31(21):3558-3560, 2015.

[14] A. Kazeroonian, F. Fr�ohlich, A. Raue, F. J. Theis, and J. Hasenauer. CERENA: ChEmical REaction Network Analyzer|a toolbox for the simulation and analysis of stochastic chemical kinetics. PloS ONE, 11(1):e0146732, 2016.

[15] T. Maiwald, H. Hass, B. Steiert, J. Vanlier, R. Engesser, A. Raue, F. Kipkeew, H. H. Bock, D. Kaschek, C. Kreutz, et al. Driving the model to its limit: Prole likelihood based model reduction. PloS ONE, 11(9):e0162366, 2016.

[16] B. Steiert, J. Timmer, and C. Kreutz. L1 regularization facilitates detection of cell type-specic parameters in dynamical systems. Bioinformatics, 32(17):i718-i726, 2016.

[17] C. Kreutz. An easy and ecient approach for testing identiability. Bioinformatics, 1:9, 2018.