Ergebnis der Recherche

Anzahl Treffer: 105

    Physikalisches Institut, Dynamische Prozesse in den Lebenswissenschaften

  1. Detailinformationen: Computational processing and error reduction strategies for standardized quantitative data in biological networks. Schilling M, Maiwald T, Bohl S, Kollmann M, Kreutz C, Timmer J, Klingmuller U: Computational processing and error reduction strategies for standardized quantitative data in biological networks. Febs J, 2005; 272 (24): 6400-6411. : http://dx.doi.org/10.1111/j.1742-4658.2005.05037.x
  2. Detailinformationen: Computational processing and error reduction strategies for standardized quantitative date in biological networks Schilling M, Maiwald T, Bohl S, Kollmann M, Kreutz C, Timmer J, Klingmüller U: Computational processing and error reduction strategies for standardized quantitative date in biological networks Febs J, 2005; 272: 6400-6411.
  3. Detailinformationen: Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2. Goerttler PS, Kreutz C, Donauer J, Faller D, Maiwald T, Marz E, Rumberger B, Sparna T, Schmitt-Graff A, Wilpert J, Timmer J, Walz G, Pahl HL: Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2. Brit J Haematol, 2005; 129 (1): 138-150. : http://dx.doi.org/10.1111/j.1365-2141.2005.05416.x
  4. Detailinformationen: Gene Expression Profiling in Polycythemia vera: Overexpression of transcription factor NF-E2 Goerttler PS, Kreutz C, Donauer J, Faller D, Maiwald T, Klein M, März E, Rumberger B, Sparna T, Schmitt-Gräff A, Wilpert J, Timmer J, Walz G, Pahl H: Gene Expression Profiling in Polycythemia vera: Overexpression of transcription factor NF-E2 Brit J Haematol, 2005; 129: 138-150.
  5. Detailinformationen: Quantitative data generation for systems biology: the impact of randomisation, calibrators and normalisers. Schilling M, Maiwald T, Bohl S, Kollmann M, Kreutz C, Timmer J, Klingmuller U: Quantitative data generation for systems biology: the impact of randomisation, calibrators and normalisers. Systems Biol, 2005; 152 (4): 193-200.
  6. Detailinformationen: Quantitative data generation for systems biology - the impact of randomisation, calibrators and normalisers Schilling M, Maiwald T, Bohl S, Kollmann M, Kreutz C, Timmer J, Klingmüller U: Quantitative data generation for systems biology - the impact of randomisation, calibrators and normalisers IEE Proc. Systems Biology, 2005; 152: 193-200.
  7. Detailinformationen: Gene profiling of polycystic kidneys Schieren G, Rumberger B, Klein M, Kreutz C, Wilpert J, Geyer M, Faller D, Timmer J, Quack I, Rump LC, Walz G, Donauer J: Gene profiling of polycystic kidneys Nephrol Dial Transpl, 2006; 21: 1816-1824.
  8. Detailinformationen: Gene profiling of polycystic kidneys. Nephrol. Dial. Transplant Schieren G., Rumberger B., Klein M., Kreutz C., Wilpert J., Geyer M., Faller D., Timmer J., Quack I., Rump L.C., Walz G., Donauer J.: Gene profiling of polycystic kidneys. Nephrol. Dial. Transplant Nephrol. Dial. Transplant., 2006; 21: 1816-1824.
  9. Detailinformationen: Host cell responses induced by Hepatisis C virus binding Fang X, Zeisel MB, Wilpert J, Gissler B, Thimme R, Kreutz C, Maiwald T, Timmer J, Kern W, Donauer J, Geyer M, Walz G, Delpa E, von Weizäcker F, Blum HE, Baumert TF: Host cell responses induced by Hepatisis C virus binding Hepatology, 2006; 43: 1326-1336.
  10. Detailinformationen: Host cell responses induced by Hepatitis C virus binding. Fang X., Zeisel M.B., Wilpert J., Gissler B., Thimme R., Kreutz C., Maiwald T., Timmer J., Kern W.V., Donauer J., Geyer M., Walz G., Delpa E., von Weizsäcker F., Blum H.E., Baumert T.F.: Host cell responses induced by Hepatitis C virus binding. Hepatology, 2006; 43: 1326-1336.
  11. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in virtro system for modelling of signal transduction pathways Klingmüller U, Bauer A, Bohl S, Nickel P, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Götschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, Mac Nelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Kleemann WJ, Zeilinger K, Heinrich M, Zanger U.M, Reuss M, Bader A, Gebhardt R, Maiwald T, Timmer J, von Weizäcker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in virtro system for modelling of signal transduction pathways IEE Proc. Systems Biology, 2006; 153: 433-447.
  12. Detailinformationen: cDNA microarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Rumberger B, Vonend O, Kreutz C, Wilpert J, Donauer J, Amann K, Rohrbach R, Timmer J, Walz G, Gerke P: cDNA microarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Kidney Blood Press Res, 2007; 30 (6): 377-387. : http://dx.doi.org/10.1159/000108624
  13. Detailinformationen: Data-based identifiability analysis of non-linear dynamical models. Hengl S, Kreutz C, Timmer J, Maiwald T: Data-based identifiability analysis of non-linear dynamical models. Bioinformatics, 2007; 23 (19): 2612-2618. : http://dx.doi.org/10.1093/bioinformatics/btm382
  14. Detailinformationen: Genome-wide analysis of DNA copy number changes and LOH in CLL using high-density SNP arrays. Pfeifer D, Pantic M, Skatulla I, Rawluk J, Kreutz C, Martens UM, Fisch P, Timmer J, Veelken H: Genome-wide analysis of DNA copy number changes and LOH in CLL using high-density SNP arrays. Blood, 2007; 109 (3): 1202-1210. : http://dx.doi.org/10.1182/blood-2006-07-034256
  15. Detailinformationen: Genome-wide analysis of DNA copy number changes in CLL using high-density SNP arrays Pfeifer D, Pantic M, Skatulla J, Rawluk J, Kreutz C, Martens U, Fisch P, Timmer J, Veelken H: Genome-wide analysis of DNA copy number changes in CLL using high-density SNP arrays Blood, 2007; 109: 1202-1210.
  16. Detailinformationen: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells. Lindenmeyer MT, Kern C, Sparna T, Donauer J, Wilpert J, Schwager J, Porath D, Kreutz C, Timmer J, Merfort I: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells. Life Sci, 2007; 80 (17): 1608-1618. : http://dx.doi.org/10.1016/j.lfs.2007.01.036
  17. Detailinformationen: A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens. Lassmann S, Kreutz C, Schoepflin A, Hopt U, Timmer J, Werner M: A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens. J Mol Med, 2009; 87 (2): 211-224. : http://dx.doi.org/10.1007/s00109-008-0419-y
  18. Detailinformationen: Combination of immunosuppressive drugs leaves specific ''fingerprint'' on gene expression in vitro B. Rumberger, C. Kreutz, C. Nickel, M. Klein, S. Lagoutte, S. Teschner, J. Timmer, G. Walz: Combination of immunosuppressive drugs leaves specific ''fingerprint'' on gene expression in vitro Immunopharmacology Immunotoxicology, 2009; 31: 283-292.
  19. Detailinformationen: Estimating of gene induction enables a relevance-based ranking of genes sets. Bartholome K., Kreutz C., Timmer J.: Estimating of gene induction enables a relevance-based ranking of genes sets. J. Comp. Biol., 2009; 16: 959-967 .
  20. Detailinformationen: Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Raue A, Kreutz C, Maiwald T, Bachmann J, Schilling M, Klingmuller U, Timmer J: Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 2009; 25 (15): 1923-1929. : http://dx.doi.org/10.1093/bioinformatics/btp358
  21. Detailinformationen: Systems biology: experimental design. Kreutz C, Timmer J: Systems biology: experimental design. FEBS J, 2009; 276 (4): 923-942. : http://dx.doi.org/10.1111/j.1742-4658.2008.06843.x
  22. Detailinformationen: Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytesHepatology Zellmer, S., Schmidt-Heck, W., Godoy, P., Weng, H., Meyer, C., Lehmann, T., Sparna, T., Schormann, W., Hammad, S., Kreutz, C., Timmer, J., von Weizsacker, F., Thurmann, P. A., Merfort, I., Guthke, R., Dooley, S., Hengstler, J. G., Gebhardt, R.: Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytes Hepatology, 2010; 52 (6): 2127-36. : http://www.ncbi.nlm.nih.gov/pubmed/20979052
  23. Detailinformationen: Addressing parameter identifiability by model-based experimentation. Raue A, Kreutz C, Maiwald T, Klingmuller U, Timmer J: Addressing parameter identifiability by model-based experimentation. Iet Syst Biol, 2011; 5 (2): 120-130. : http://dx.doi.org/10.1049/iet-syb.2010.0061
  24. Detailinformationen: Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Bachmann J, Raue A, Schilling M, Bohm ME, Kreutz C, Kaschek D, Busch H, Gretz N, Lehmann WD, Timmer J, Klingmuller U: Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Mol Syst Biol, 2011; 7: 516-516. : http://dx.doi.org/10.1038/msb.2011.50
  25. Detailinformationen: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Ferreira KS, Kreutz C, Macnelly S, Neubert K, Haber A, Bogyo M, Timmer J, Borner C: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Apoptosis, 2012; 17 (5): 503-515. : http://dx.doi.org/10.1007/s10495-011-0691-0
  26. Detailinformationen: Comprehensive estimation of input signals and dynamics in biochemical reaction networks. Schelker M, Raue A, Timmer J, Kreutz C: Comprehensive estimation of input signals and dynamics in biochemical reaction networks. Bioinformatics, 2012; 28 (18): i529-i534. : http://dx.doi.org/10.1093/bioinformatics/bts393
  27. Detailinformationen: Experimental design for parameter estimation of gene regulatory networks. Steiert B, Raue A, Timmer J, Kreutz C: Experimental design for parameter estimation of gene regulatory networks. Plos One, 2012; 7 (7): e40052-e40052. : http://dx.doi.org/10.1371/journal.pone.0040052
  28. Detailinformationen: Likelihood based observability analysis and confidence intervals for predictions of dynamic models. Kreutz C, Raue A, Timmer J: Likelihood based observability analysis and confidence intervals for predictions of dynamic models. Bmc Syst Biol, 2012; 6: 120-120. : http://dx.doi.org/10.1186/1752-0509-6-120
  29. Detailinformationen: TSSi-an R package for transcription start site identification from 5' mRNA tag data. Kreutz C, Gehring JS, Lang D, Reski R, Timmer J, Rensing SA: TSSi-an R package for transcription start site identification from 5' mRNA tag data. Bioinformatics, 2012; 28 (12): 1641-1642. : http://dx.doi.org/10.1093/bioinformatics/bts189
  30. Detailinformationen: Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability. Raue A, Kreutz C, Theis FJ, Timmer J: Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability. Philos T Roy Soc A, 2013; 371 (1984): 20110544-20110544. : http://dx.doi.org/10.1098/rsta.2011.0544
  31. Detailinformationen: Lessons learned from quantitative dynamical modeling in systems biology. Raue A, Schilling M, Bachmann J, Matteson A, Schelke M, Kaschek D, Hug S, Kreutz C, Harms BD, Theis FJ, Klingmuller U, Timmer J: Lessons learned from quantitative dynamical modeling in systems biology. Plos One, 2013; 8 (9): e74335-e74335. : http://dx.doi.org/10.1371/journal.pone.0074335
  32. Detailinformationen: MeDIP coupled with a promoter tiling array as a platform to investigate global DNA methylation patterns in AML cells. Yalcin A, Kreutz C, Pfeifer D, Abdelkarim M, Klaus G, Timmer J, Lubbert M, Hackanson B: MeDIP coupled with a promoter tiling array as a platform to investigate global DNA methylation patterns in AML cells. Leukemia Res, 2013; 37 (1): 102-111. : http://dx.doi.org/10.1016/j.leukres.2012.09.014
  33. Detailinformationen: Profile likelihood in systems biology. Kreutz C, Raue A, Kaschek D, Timmer J: Profile likelihood in systems biology. Febs J, 2013; 280 (11): 2564-2571. : http://dx.doi.org/10.1111/febs.12276
  34. Detailinformationen: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates prefibrotic primary myelofibrosis from essential thrombocythemia. Aumann K, Frey AV, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates prefibrotic primary myelofibrosis from essential thrombocythemia. Blood, 2013; 122 (1): 93-99. : http://dx.doi.org/10.1182/blood-2012-11-463257
  35. Detailinformationen: Cause and cure of sloppiness in ordinary differential equation models. Tonsing C, Timmer J, Kreutz C: Cause and cure of sloppiness in ordinary differential equation models. Phys Rev E, 2014; 90 (2-1): 023303-023303.
  36. Detailinformationen: Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach. Meyer P, Cokelaer T, Chandran D, Kim KH, Loh PR, Tucker G, Lipson M, Berger B, Kreutz C, Raue A, Steiert B, Timmer J, Bilal E, Sauro HM, Stolovitzky G, Saez-Rodriguez J: Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach. Bmc Syst Biol, 2014; 8 (1): 13-13. : http://dx.doi.org/10.1186/1752-0509-8-13
  37. Detailinformationen: PI3K-p110-alpha-subtype signalling mediates survival, proliferation and neurogenesis of cortical progenitor cells via activation of mTORC2. Wahane SD, Hellbach N, Prentzell MT, Weise SC, Vezzali R, Kreutz C, Timmer J, Krieglstein K, Thedieck K, Vogel T: PI3K-p110-alpha-subtype signalling mediates survival, proliferation and neurogenesis of cortical progenitor cells via activation of mTORC2. J Neurochem, 2014; 130 (2): 255-267. : http://dx.doi.org/10.1111/jnc.12718
  38. Detailinformationen: Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Raue A, Steiert B, Schelker M, Kreutz C, Maiwald T, Hass H, Vanlier J, Tonsing C, Adlung L, Engesser R, Mader W, Heinemann T, Hasenauer J, Schilling M, Hofer T, Klipp E, Theis F, Klingmuller U, Schoberl B, Timmer J: Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics, 2015; 31 (21): 3558-3560. : http://dx.doi.org/10.1093/bioinformatics/btv405
  39. Detailinformationen: Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations. Schwen LO, Schenk A, Kreutz C, Timmer J, Bartolome Rodriguez MM, Kuepfer L, Preusser T: Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations. Plos One, 2015; 10 (7): e0133653-e0133653. : http://dx.doi.org/10.1371/journal.pone.0133653
  40. Detailinformationen: Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. Karr JR, Williams AH, Zucker JD, Raue A, Steiert B, Timmer J, Kreutz C, Wilkinson S, Allgood BA, Bot BM, Hoff BR, Kellen MR, Covert MW, Stolovitzky GA, Meyer P: Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. Plos Comput Biol, 2015; 11 (5): e1004096-e1004096. : http://dx.doi.org/10.1371/journal.pcbi.1004096
  41. Detailinformationen: USP18 lack in microglia causes destructive interferonopathy of the mouse brain. Goldmann T, Zeller N, Raasch J, Kierdorf K, Frenzel K, Ketscher L, Basters A, Staszewski O, Brendecke SM, Spiess A, Tay TL, Kreutz C, Timmer J, Mancini GM, Blank T, Fritz G, Biber K, Lang R, Malo D, Merkler D, Heikenwalder M, Knobeloch KP, Prinz M: USP18 lack in microglia causes destructive interferonopathy of the mouse brain. Embo J, 2015; 34 (12): 1612-1629. : http://dx.doi.org/10.15252/embj.201490791
  42. Detailinformationen: A Thymic Epithelial Stem Cell Pool Persists throughout Ontogeny and Is Modulated by TGF-beta. Ucar O, Li K, Dvornikov D, Kreutz C, Timmer J, Matt S, Brenner L, Smedley C, Travis MA, Hofmann TG, Klingmuller U, Kyewski B: A Thymic Epithelial Stem Cell Pool Persists throughout Ontogeny and Is Modulated by TGF-beta. Cell Rep, 2016; 17 (2): 448-457. : http://dx.doi.org/10.1016/j.celrep.2016.09.027
  43. Detailinformationen: Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease. Binder H, Kurz T, Teschner S, Kreutz C, Geyer M, Donauer J, Kraemer-Guth A, Timmer J, Schumacher M, Walz G: Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease. Bmc Med Genomics, 2016; 9 (1): 43-43. : http://dx.doi.org/10.1186/s12920-016-0210-9
  44. Detailinformationen: Driving the Model to Its Limit: Profile Likelihood Based Model Reduction. Maiwald T, Hass H, Steiert B, Vanlier J, Engesser R, Raue A, Kipkeew F, Bock HH, Kaschek D, Kreutz C, Timmer J: Driving the Model to Its Limit: Profile Likelihood Based Model Reduction. Plos One, 2016; 11 (9): e0162366-e0162366. : http://dx.doi.org/10.1371/journal.pone.0162366
  45. Detailinformationen: Fast integration-based prediction bands for ordinary differential equation models. Hass H, Kreutz C, Timmer J, Kaschek D: Fast integration-based prediction bands for ordinary differential equation models. Bioinformatics, 2016. : http://dx.doi.org/10.1093/bioinformatics/btv743
  46. Detailinformationen: Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells. Merkle R, Steiert B, Salopiata F, Depner S, Raue A, Iwamoto N, Schelker M, Hass H, Wasch M, Bohm ME, Mucke O, Lipka DB, Plass C, Lehmann WD, Kreutz C, Timmer J, Schilling M, Klingmuller U: Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells. Plos Comput Biol, 2016; 12 (8): e1005049-e1005049. : http://dx.doi.org/10.1371/journal.pcbi.1005049
  47. Detailinformationen: L1 regularization facilitates detection of cell type-specific parameters in dynamical systems. Steiert B, Timmer J, Kreutz C: L1 regularization facilitates detection of cell type-specific parameters in dynamical systems. Bioinformatics, 2016; 32 (17): i718-i726. : http://dx.doi.org/10.1093/bioinformatics/btw461
  48. Detailinformationen: Partial break in tolerance of NKG2A-/LIR-1- single KIR+ NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Rathmann S, Keck C, Kreutz C, Weit N, Muller M, Timmer J, Glatzel S, Follo M, Malkovsky M, Werner M, Handgretinger R, Finke J, Fisch P: Partial break in tolerance of NKG2A-/LIR-1- single KIR+ NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Bone Marrow Transpl, 2017; 52 (8): 1144-1155. : http://dx.doi.org/10.1038/bmt.2017.81
  49. Detailinformationen: Profile likelihood-based analyses of infectious disease models. Tonsing C, Timmer J, Kreutz C: Profile likelihood-based analyses of infectious disease models. Stat Methods Med Res, 2018; 27 (7): 1979-1998. : http://dx.doi.org/10.1177/0962280217746444
  50. Detailinformationen: Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression. Lucarelli P, Schilling M, Kreutz C, Vlasov A, Boehm ME, Iwamoto N, Steiert B, Lattermann S, Wasch M, Stepath M, Matter MS, Heikenwalder M, Hoffmann K, Deharde D, Damm G, Seehofer D, Muciek M, Gretz N, Lehmann WD, Timmer J, Klingmuller U: Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression. Cell Syst, 2018; 6 (1): 75-89.e11. : http://dx.doi.org/10.1016/j.cels.2017.11.010
  51. Detailinformationen: Benchmark problems for dynamic modeling of intracellular processes. Hass H, Loos C, Raimundez-Alvarez E, Timmer J, Hasenauer J, Kreutz C: Benchmark problems for dynamic modeling of intracellular processes. Bioinformatics, 2019; 35 (17): 3073-3082. : http://dx.doi.org/10.1093/bioinformatics/btz020
  52. Detailinformationen: Functional Proteomics of Breast Cancer Metabolism Identifies GLUL as Responder during Hypoxic Adaptation. Bernhardt S, Tonsing C, Mitra D, Erdem N, Muller-Decker K, Korf U, Kreutz C, Timmer J, Wiemann S: Functional Proteomics of Breast Cancer Metabolism Identifies GLUL as Responder during Hypoxic Adaptation. J Proteome Res, 2019; 18 (3): 1352-1362. : http://dx.doi.org/10.1021/acs.jproteome.8b00944
  53. Detailinformationen: Optimal paths between Parameter Estimates in Non-linear ODE Systems Using the nudged Elastic Band Method Kreutz C, Tönsing C, Timmer J: Optimal paths between Parameter Estimates in Non-linear ODE Systems Using the nudged Elastic Band Method ORIGINAL RESEARCHpublished: 09 October 2019doi: 10.3389/fphy.2019.00149Frontiers in Physics, 2019; 7 Suppl. 149: 1-14. : http://10.3389/fphy.2019.00149

    Department für Pathologie, Institut für Klinische Pathologie

  1. Detailinformationen: Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2. Goerrtler PS, Kreutz C, Donauer J, Faller D, Maiwald T, Marz E, Rumberger B, Sparna T, Schmitt-Graeff A, Wilpert J, Timmer J, Walz g, Pahl HL: Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2. Brit J Haematol, 2005; 129 (1): 138-150.
  2. Detailinformationen: An error model for protein quantification. Kreutz C, Bartolome Rodriguez MM, Maiwald T, Seidl M, Blum HE, Mohr L, Timmer J: An error model for protein quantification. Bioinformatics, 2007; 23 (20): 2747-2753. : http://dx.doi.org/10.1093/bioinformatics/btm397
  3. Detailinformationen: An error model for protein quantification. Kreutz C, Bartolome Rodriguez MM, Maiwald T, Seidl M, Blum HE, Mohr L, Timmer J: An error model for protein quantification. Bioinformatics, 2007; 23 (20): 2747-2753. : http://dx.doi.org/10.1093/bioinformatics/btm397
  4. Detailinformationen: An error model for protein quantification. Kreutz C, Bartolome Rodriguez MM, Maiwald T, Seidl M, Blum HE, Mohr L, Timmer J: An error model for protein quantification. Bioinformatics, 2007; 23 (20): 2747-2753. : http://dx.doi.org/10.1093/bioinformatics/btm397
  5. Detailinformationen: cDNA microarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Rumberger B, Vonend O, Kreutz C, Wilpert J, Donauer J, Amann K, Rohrbach R, Timmer J, Walz G, Gerke P: cDNA microarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Kidney Blood Press R, 2007; 30 (6): 377-387.
  6. Detailinformationen: Genome-wide analysis of DNA copy number changes and LOH in CLL using high-density SNP arrays. Pfeifer D, Pantic M, Skatulla I, Rawluk J, Kreutz C, Martens UM, Fisch P, Timmer J, Veelken H: Genome-wide analysis of DNA copy number changes and LOH in CLL using high-density SNP arrays. Blood, 2007; 109 (3): 1202-1210.
  7. Detailinformationen: A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens. Lassmann S, Kreutz C, Schoepflin A, Hopt U, Timmer J, Werner M: A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens. J Mol Med-jmm, 2009; 87 (2): 211-224. : http://dx.doi.org/10.1007/s00109-008-0419-y
  8. Detailinformationen: [Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis]. Aumann K, Frey AV, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: [Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis]. Pathologe, 2013; 34 Suppl 2: 201-209. : http://dx.doi.org/10.1007/s00292-013-1824-8
  9. Detailinformationen: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates pre-fibrotic primary myelofibrosis from essential thrombocythemia. Aumann K, Frey AV, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates pre-fibrotic primary myelofibrosis from essential thrombocythemia. Blood, 2013; 122 (1): 93-99. : http://dx.doi.org/10.1182/blood-2012-11-463257
  10. Detailinformationen: Partial break in tolerance of NKG2A(-)/LIR-1(-) single KIR(+) NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Rathmann S, Keck C, Kreutz C, Weit N, Muller M, Timmer J, Glatzel S, Follo M, Malkovsky M, Werner M, Handgretinger R, Finke J, Fisch P: Partial break in tolerance of NKG2A(-)/LIR-1(-) single KIR(+) NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Bone Marrow Transpl, 2017; 52 (8): 1144-1155. : http://dx.doi.org/10.1038/bmt.2017.81
  11. Detailinformationen: BRAF V600E Mutations in Nevi and Melanocytic Tumors of Uncertain Malignant Potential. Seitz-Alghrouz R, Hidalgo JV, Kayser C, Kreutz C, Technau-Hafsi K, Diaz C, von Deimling A, Timmer J, Werner M, Malkovsky M, Fisch P: BRAF V600E Mutations in Nevi and Melanocytic Tumors of Uncertain Malignant Potential. J Invest Dermatol, 2018; 138 (11): 2489-2491. : http://dx.doi.org/10.1016/j.jid.2018.04.035

    Department Innere Medizin, Klinik für Innere Medizin I

  1. Detailinformationen: Genome-wide analysis of DNA copy number changes and LOH in CLL using Pfeifer D, Pantic M, Skatulla I, Rawluk J, Kreutz C, Martens UM, Fisch P, Timmer J, Veelken H: Genome-wide analysis of DNA copy number changes and LOH in CLL using Blood, 2006 (online). (in Druck)
  2. Detailinformationen: Genome-wide analysis of DNA copy number changes and LOH in CLL using Pfeifer D, Pantic M, Skatulla I, Rawluk J, Kreutz C, Martens UM, Fisch P, Timmer J, Veelken H: Genome-wide analysis of DNA copy number changes and LOH in CLL using Blood, 2007; 109 (3): 1202-1210.
  3. Detailinformationen: [Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis]. Aumann K, Frey AV, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: [Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis]. Pathologe, 2013; 34 Suppl. 2: 201-209. : http://dx.doi.org/10.1007/s00292-013-1824-8
  4. Detailinformationen: MeDIP coupled with a promoter tiling array as a platform to investigate global DNA methylation patterns in AML cells. Yalcin A, Kreutz C, Pfeifer D, Abdelkarim M, Klaus G, Timmer J, Lubbert M, Hackanson B: MeDIP coupled with a promoter tiling array as a platform to investigate global DNA methylation patterns in AML cells. Leukemia Res, 2013; 37 (1): 102-111. : http://dx.doi.org/10.1016/j.leukres.2012.09.014
  5. Detailinformationen: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates prefibrotic primary myelofibrosis from essential thrombocythemia. Aumann K, Frey AV, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates prefibrotic primary myelofibrosis from essential thrombocythemia. Blood, 2013; 122 (1): 93-99. : http://dx.doi.org/10.1182/blood-2012-11-463257
  6. Detailinformationen: Hepatocyte Ploidy Is a Diversity Factor for Liver Homeostasis. Kreutz C, MacNelly S, Follo M, Waldin A, Binninger-Lacour P, Timmer J, Bartolome-Rodriguez MM: Hepatocyte Ploidy Is a Diversity Factor for Liver Homeostasis. Front Physiol, 2017; 8: 862-862. : http://dx.doi.org/10.3389/fphys.2017.00862
  7. Detailinformationen: Partial break in tolerance of NKG2A(-)/LIR-1(-) single KIR(+) NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Rathmann S, Keck C, Kreutz C, Weit N, Muller M, Timmer J, Glatzel S, Follo M, Malkovsky M, Werner M, Handgretinger R, Finke J, Fisch P: Partial break in tolerance of NKG2A(-)/LIR-1(-) single KIR(+) NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation. Bone Marrow Transpl, 2017; 52 (8): 1144-1155. : http://dx.doi.org/10.1038/bmt.2017.81

    Department Innere Medizin, Klinik für Innere Medizin IV

  1. Detailinformationen: Gene expression profiling in polycythaemia vera; overexpression of transcription factor NF-E2. Goerttler PS, Kreutz C, Donauer J, Faller D, Maiwald T, Marz E, Rumberger B, Sparna T, Schmitt-Graff A, Wilpert J, Timmer J, Walz G, Pahl HL: Gene expression profiling in polycythaemia vera; overexpression of transcription factor NF-E2. Brit J Haematol, 2005; 129 (1): 138-150.
  2. Detailinformationen: Gene Profiling in polycystic kidney disease. Schieren G, Rumberger B, wilpert J, Geyer M, Klein M, Faller D, Kreutz C, Timmer J, Walz G, Donauer J: Gene Profiling in polycystic kidney disease. Nephrol Dial Transpl, 2006; 21 (7): 1816-1824.
  3. Detailinformationen: Horst Cell Responses Induced by Hepatitis C virus Binding. Fang X, Wilpert J, Barth H, Gissler B, Kreutz C, Timmer J, Kern WV, Donauer J, Walz G, von Weizsäcker F, Blum HE, Baumert TF: Horst Cell Responses Induced by Hepatitis C virus Binding. Hepatology, 2006; 43 (6): 1326-1336.
  4. Detailinformationen: Primary mouse hepatocytes for system biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Klingmuller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Gotschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer S, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizacker F, Hengstler JG: Primary mouse hepatocytes for system biology approaches: a standardized in vitro system for modelling of signal transduction pathways. IEE Proc Syst Biol, 2006; 153 (6): 433-447.
  5. Detailinformationen: cDNA micoarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Rumberger B, Vonend O, Kreutz C, Wilpert J, Donauer J, Amann K, Rohrbach R, Timmer J, Walz G, Gerke P: cDNA micoarray analysis of adaptive changes after renal ablation in a sclerosis-resistant mouse strain. Kidney Blood Press R, 2007; 30 (6): 377-387.
  6. Detailinformationen: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells. Lindenmeyer MT, Kern C, Sparna T, Donauer J, Wilpert J, Schwager J, Porath D, Kreutz C, Timmer J, Merfort I: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells. Life Sci, 2007; 3 (80): 1608-1618.
  7. Detailinformationen: Combination of immunosuppressive drugs leaves specific "fingerprint" on gene expression in vitro. Rumberger B, Kreutz C, Nickel C, Klein M, Lagoutte S, Teschner S, Timmer J, Gerke P, Walz G, Donauer J: Combination of immunosuppressive drugs leaves specific "fingerprint" on gene expression in vitro. Int Immunopharmacol, 2009; 9: 1-10.

    Klinik für Anästhesiologie und Intensivmedizin, Universitätsklinikum Freiburg

  1. Detailinformationen: Gene Expression Profiling in Polycythemia vera: Overexpression of transcription factor NF-E2 Goerttler PS, Kreutz C, Donauer J, Faller D, Maiwald T, März E, Rumberger B, Sparna T, Schmitt-Gräff A, Wilpert J, Timmer J, Walz G, Pahl HL: Gene Expression Profiling in Polycythemia vera: Overexpression of transcription factor NF-E2 Brit J Haematol, 2005; 129: 138-150.

    Institut für Molekulare Medizin und Zellforschung (IMMZ), Zentrum für Biochemie und Molekulare Zellforschung (ZBMZ)

  1. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Klingmüller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Götschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizsäcker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. IEE Proc Syst Biol, 2006; 153 (6): 433-447.
  2. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Klingmuller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Gotschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizsacker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Systems Biol, 2006; 153 (6): 433-447.
  3. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Klingmuller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Gotschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizsacker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Systems Biol, 2006; 153 (6): 433-447.
  4. Detailinformationen: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Ferreira KS, Kreutz C, Macnelly S, Neubert K, Haber A, Bogyo M, Timmer J, Borner C: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Apoptosis, 2012; 17 (5): 503-515. : http://dx.doi.org/10.1007/s10495-011-0691-0
  5. Detailinformationen: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Ferreira KS, Kreutz C, Macnelly S, Neubert K, Haber A, Bogyo M, Timmer J, Borner C: Caspase-3 feeds back on caspase-8, Bid and XIAP in type I Fas signaling in primary mouse hepatocytes. Apoptosis, 2012; 17 (5): 503-515. : http://dx.doi.org/10.1007/s10495-011-0691-0

    Department Innere Medizin, Klinik für Innere Medizin II

  1. Detailinformationen: Host cell responses induced by hepatitis C virus binding. Fang X, Zeisel MB, Wilpert J, Gissler B, Thimme R, Kreutz C, Maiwald T, Timmer J, Kern WV, Donauer J, Geyer M, Walz G, Depla E, von Weizsacker F, Blum HE, Baumert TF: Host cell responses induced by hepatitis C virus binding. Hepatology, 2006; 43 (6): 1326-1336.
  2. Detailinformationen: Hepatocyte Ploidy Is a Diversity Factor for Liver Homeostasis. Kreutz C, MacNelly S, Follo M, Waldin A, Binninger-Lacour P, Timmer J, Bartolome-Rodriguez MM: Hepatocyte Ploidy Is a Diversity Factor for Liver Homeostasis. Front Physiol, 2017; 8 (online): 862-862. : http://dx.doi.org/10.3389/fphys.2017.00862

    Institut für Pharmazeutische Wissenschaften, Arbeitskreis Prof. Dr. Irmgard Merfort

  1. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways Klingmüller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Götschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizsäcker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways Systems Biology, 2006; 153: 433-447.
  2. Detailinformationen: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells LINDENMEYER, M.T., KERN, C.,, SPARNA, T., DONAUER, J.,, WILPERT, J.,, SCHWAGER, J.,, PORATH, D.,, KREUTZ; C.,, TIMMER, J.,, MERFORT, I.: Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells Life Sci, 2007; 80: 1608-1618.
  3. Detailinformationen: Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytes. Zellmer S, Schmidt-Heck W, Godoy P, Weng H, Meyer C, Lehmann T, Sparna T, Schormann W, Hammad S, Kreutz C, Timmer J, von Weizsacker F, Thurmann PA, Merfort I, Guthke R, Dooley S, Hengstler JG, Gebhardt R: Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytes. Hepatology, 2010; 52 (6): 2127-2136. : http://dx.doi.org/10.1002/hep.23930

    Freiburger Materialforschungszentrum (FMF)

  1. Detailinformationen: Einführung in die numerischen Methoden der Physik Breuer,Heinz- Peter, Liehr,Andreas W., Kreutz,Clemens, Geier,Florian: Einführung in die numerischen Methoden der Physik Vorlesungsmanuskript, 2005. : http://webber.physik.uni-freiburg.de/~breuer/matlab-kurs/index.html

    FRIAS School of Life Sciences (Fellows 2008-2013)

  1. Detailinformationen: Combination of immunosuppressive drugs leaves specific "fingerprint" on gene expression in vitro B. Rumberger, C. Kreutz, C. Nickel, M. Klein, S. Lagoutte, S. Teschner, J. Timmer, P. Gerke, G. Walz, J. Donauer: Combination of immunosuppressive drugs leaves specific "fingerprint" on gene expression in vitro Immunopharmacology and Immunotoxicology, 2009; 31 (2): 283-292.

    Institut für Medizinische Biometrie und Statistik

  1. Detailinformationen: Differenzialdiagnose myelproliferativer Neoplasien. Aumann K, Frey A-V, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: Differenzialdiagnose myelproliferativer Neoplasien. Pathologe, 2013; 34 Suppl. 2: 201-209. : http://dx.doi.org/10.1007/s00292-013-1824-8
  2. Detailinformationen: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates pre-fibrotic primary myelofibrosis from essential thrombocythemia. Aumann K, Frey A-V, May AM, Hauschke D, Kreutz C, Marx JP, Timmer J, Werner M, Pahl HL: Subcellular mislocalization of the transcription factor NF-E2 in erythroid cells discriminates pre-fibrotic primary myelofibrosis from essential thrombocythemia. Blood, 2013; 122 (1): 93-99. : http://dx.doi.org/10.1182/blood-2012-11-463257
  3. Detailinformationen: Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease. Binder H, Kurz T, Teschner S, Kreutz C, Geyer M, Donauer J, Kraemer-Guth A, Timmer J, Schumacher M, Walz G: Dealing with prognostic signature instability: a strategy illustrated for cardiovascular events in patients with end-stage renal disease. Bmc Med Genomics, 2016; 9 (online): 43. : http://dx.doi.org/10.1186/s12920-016-0210-9
  4. Detailinformationen: An easy and efficient approach for testing identifiability. Kreutz C: An easy and efficient approach for testing identifiability. Bioinformatics, 2018; 34 (11): 1913-1921. : http://dx.doi.org/10.1093/bioinformatics/bty035
  5. Detailinformationen: Quantifying post-transcriptional regulation in the development of Drosophila melanogaster. Becker K, Bluhm A, Casas-Vila N, Dinges N, Dejung M, Sayols S, Kreutz C, Roignant JY, Butter F, Legewie S: Quantifying post-transcriptional regulation in the development of Drosophila melanogaster. Nat Commun, 2018; 9 (1) (online): 4970-4970. : http://dx.doi.org/10.1038/s41467-018-07455-9
  6. Detailinformationen: Optimal Paths Between Parameter Estimates in Non-linear ODE Systems Using the Nudged Elastic Band Method. Tönsing C, Timmer J, Kreutz C: Optimal Paths Between Parameter Estimates in Non-linear ODE Systems Using the Nudged Elastic Band Method. Frontiers in Physics, 2019; 7 (online): 149. : https://doi.org/10.3389/fphy.2019.00149
  7. Detailinformationen: Recipes for Analysis of Molecular Networks Using the Data2Dynamics Modeling Environment. Steiert B, Kreutz C, Raue A, Timmer J: Recipes for Analysis of Molecular Networks Using the Data2Dynamics Modeling Environment. Methods in Molecular Biology, 2019; 1945: 341-362. : https://doi.org/10.1007/978-1-4939-9102-0_16

    Institut für Anatomie und Zellbiologie, Abteilung Molekulare Embryologie

  1. Detailinformationen: PI3K-p110-alpha-subtype signalling mediates survival, proliferation and neurogenesis of cortical progenitor cells via activation of mTORC2. Wahane SD, Hellbach N, Prentzell MT, Weise SC, Vezzali R, Kreutz C, Timmer J, Krieglstein K, Thedieck K, Vogel T: PI3K-p110-alpha-subtype signalling mediates survival, proliferation and neurogenesis of cortical progenitor cells via activation of mTORC2. J Neurochem, 2014; 130 (2): 255-267. : http://dx.doi.org/10.1111/jnc.12718

    Zentrum für Psychische Erkrankungen (Department), Klinik für Psychiatrie und Psychotherapie

  1. Detailinformationen: USP 18 lack in microglia causes destructive interferonopathy of the mouse brain Goldmann, T, Zeller, N, Raasch, J, Kierdorf, K, Frenzel, K, Ketscher, L, Basters, A, Staszewski, O, Brendecke, SM, Spiess, A, Tay, TL, Kreutz, C, Timmer, J, Mancini, GM, Blank, T, Fritz, G, Biber, K, Lang, R, Malo, D, Merkler, D, Heikenwälder, M, Knobeloch, KP, Prinz, M: USP 18 lack in microglia causes destructive interferonopathy of the mouse brain Embo J, 2015; 34: 1612-1629.

    Department Neurozentrum, Institut für Neuropathologie

  1. Detailinformationen: USP18 lack in microglia causes destructive interferonopathy of the mouse brain. Goldmann T, Zeller N, Raasch J, Kierdorf K, Frenzel K, Ketscher L, Basters A, Staszewski O, Brendecke SM, Spiess A, Tay TL, Kreutz C, Timmer J, Mancini GM, Blank T, Fritz G, Biber K, Lang R, Malo D, Merkler D, Heikenwalder M, Knobeloch KP *, Prinz M *: USP18 lack in microglia causes destructive interferonopathy of the mouse brain. Embo J, 2015; 34 (12): 1612-1629. : http://dx.doi.org/10.15252/embj.201490791

    Bernstein Center Freiburg

  1. Detailinformationen: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Klingmüller U, Bauer A, Bohl S, Nickel PJ, Breitkopf K, Dooley S, Zellmer S, Kern C, Merfort I, Sparna T, Donauer J, Walz G, Geyer M, Kreutz C, Hermes M, Götschel F, Hecht A, Walter D, Egger L, Neubert K, Borner C, Brulport M, Schormann W, Sauer C, Baumann F, Preiss R, MacNelly S, Godoy P, Wiercinska E, Ciuclan L, Edelmann J, Zeilinger K, Heinrich M, Zanger UM, Gebhardt R, Maiwald T, Heinrich R, Timmer J, von Weizsäcker F, Hengstler JG: Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways. Systems Biol, 2006; 153 (6): 433-447.

    FRIAS Natur- und Ingenieurwissenschaften und Medizin (Fellows ab 2013)

  1. Detailinformationen: Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability Raue A, Kreutz C, Theis F, Timmer J: Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2013; 371 (1984). : http://dx.doi.org/10.1098/rsta.2011.0544
  2. Detailinformationen: Profile likelihood in systems biology Kreutz C, Raue A, Kaschek D, Timmer J: Profile likelihood in systems biology FEBS JOURNAL, 2013; 280 (11): 2564-2571. : http://dx.doi.org/10.1111/febs.12276
  3. Detailinformationen: Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. Karr JR, Williams AH, Zucker JD, Raue A, Steiert B, Timmer J, Kreutz C, Wilkinson S, Allgood BA, Bot BM, Hoff BR, Kellen MR, Covert MW, Stolovitzky GA, Meyer P: Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. Plos Comput Biol, 2015; 11 (5): e1004096-e1004096. : http://dx.doi.org/10.1371/journal.pcbi.1004096