Head of the Group

Dr.-Ing. Steffen Klamt
Dr.-Ing. Steffen Klamt
Phone: +49 391 6110 480
Fax: +49 391 6110 509

Contact Person

Anke Goettert
Phone: +49 391 6110 477
Fax: +49 391 6110 452

Group page


Publications ARB group

Journal Article (90)

  1. 2017
    Harder, B.-J.; Bettenbrock, K.; Klamt, S.: Temperature-dependent dynamic control of the TCA cycle increases volumetric productivity of itaconic acid production by Escherichia coli. Biotechnology and Bioengineering, 28865130 (accepted)
  2. Hädicke, O.; Klamt, S.: EColiCore2: a reference model of the central metabolism of Escherichia coli and the relationships to its genome-scale parent model. Scientific Reports 7, 39647 (2017)
  3. Kamp von, A.; Thiele, S.; Hädicke, O.; Klamt, S.: Use of CellNetAnalyzer in biotechnology and metabolic engineering. Journal of Biotechnology 261, pp. 221 - 228 (2017)
  4. Kamp von, A.; Klamt, S.: Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms. Nature Communications 8, 15926 (2017)
  5. Klamt, S.; Regensburger, G.; Gerstl, P.M.; Jungreuthmayer, C.; Schuster, S.; Mahadevan, R.; Zanghellini, J.; Müller, S.: From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints. PLoS Computational Biology 13 (4), e1005409 (2017)
  6. Prigent, S.; Frioux, C.; Dittami, S. M.; Thiele, S.; Larhlimi, A.; Collet, G.; Gutknecht, F.; Got, J.; Eveillard, D.; Bourdon, J. et al.; Plewniak, F.; Tonon, T.; Siegel, A.: Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks. PLoS Computational Biology 13, e1005276 (2017)
  7. Zander, D.; Samaga, D.; Straube, R.; Bettenbrock, K.: Bistability and Nonmonotonic Induction of the lac Operon in the Natural Lactose Uptake System. Biophysical Journal 112 (9), pp. 1984 - 1996 (2017)
  8. 2016
    Bordron, P.; Latorre, M.; Cortés, M.-P.; González, M.; Thiele, S.; Siegel, A.; Maass, A.; Eveillard, D.: Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach. MicrobiologyOpen 5 (1), pp. 106 - 117 (2016)
  9. Gerstl, M. P.; Klamt, S.; Jungreuthmayer, C.; Zanghellini, J.: Exact quantification of cellular robustness in genome-scale metabolic networks. Bioinformatics 32 (5), pp. 730 - 737 (2016)
  10. Harder, B.-J.; Bettenbrock, K.; Klamt, S.: Model-Based metabolic engineering enables high yield itaconic acid production by Escherichia coli. Metabolic Engineering 38, pp. 29 - 37 (2016)
  11. Koch, S.; Benndorf, D.; Fronk, K.; Reichl, U.; Klamt, S.: Predicting compositions of microbial communities from stoichiometric models with applications for the biogas process. Biotechnology for Biofuels (9), 17 (2016)
  12. Kolczyk, K.; Conradi, C.: Challenges in horizontal model integration. BMC Systems Biology (10), 28 (2016)
  13. Müller, S.; Feliu, E.; Regensburger, G.; Conradi, C.; Shiu, A.; Dickenstein, A.: Sign Conditions for Injectivity of Generalized Polynomial Maps with Applications to Chemical Reaction Networks and Real Algebraic Geometry. Foundations of Computational Mathematics 16 (1), pp. 69 - 97 (2016)
  14. Ud-Dean, S.; Heise, S.; Klamt, S.; Gunawan, R.: TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments. BMC Bioinformatics 17 (17), 252 (2016)
  15. Wrzosek, K.; García Rivera, M. A.; Bettenbrock, K.; Seidel-Morgenstern, A.: Racemization of undesired enantiomers: Immobilization of mandelate racemase and application in a fixed bed reactor. Biotechnology Journal 11 (4), pp. 453 - 463 (2016)
  16. Wu, H.; Kamp von, A.; Leoncikas, V.; Mori, W.; Sahin, M.; Gevorgyan, A.; Linley, C.; Grabowski, M.; Mannan, A. A.; Stoy, N. et al.; Steward, G. R.; Ward, L. T.; Lewis, D.J.M.; Sroca, J.; Matsuno, H.; Klamt, S.; Westerhoff, H.V.; McFadden, J.; Plant, N.J.; Kierzek, A.M.: MUFINS: multi-formalism interaction network simulator. npj Systems Biology and Applications 2, 16032 (2016)
  17. 2015
    Bastiaens, P. I.H.; Birtwistle, M.; Blüthgen, N.; Bruggeman, F.; Cho, K.-H.; de la Fuente, A.; Hoek, J.; Kiyatkin, A.; Klamt, S.; Kolch, W. et al.; Legewie, S.; Mendes, P.; Naka, T.; Santra, T.; Sontag, E.; Westerhoff, H.; Kholodenko, B.: Silence on the relevant literature and errors in implementation. Nature Biotechnology 33 (4), pp. 336 - 339 (2015)
  18. Conradi, C.; Shiu, A.: A Global Convergence Result for Processive Multisite Phosphorylation Systems. Bulletin of mathematical biology 77 (1), pp. 126 - 155 (2015)
  19. D`Allessandro, L. A.; Samaga, R.; Maiwald, T.; Rho, S.-H.; Bonefas, S.; Raue, A.; Iwamoto, N.; Kienast, A.; Waldow, K.; Meyer, R. et al.; Schilling, M.; Timmer, J.; Klamt, S.; Klingmüller, U.: Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. PLoS Computational Biology 11 (4), e1004192 (2015)
  20. Erdrich, P.; Steuer, R.; Klamt, S.: An algorithm for the reduction of genome-scale metabolic network models to meaningful core models. BMC Systems Biology 9, 48 (2015)
  21. Hädicke, O.; Bettenbrock, K.; Klamt, S.: Enforced ATP futile cycling increases specific productivity and yield of anaerobic lactate production in Escherichia coli. Biotechnology and Bioengineering 112 (10), pp. 2195 - 2199 (2015)
  22. Hädicke, O.; Klamt, S.: Manipulation of the ATP pool as a tool for metabolic engineering. Biochemical Society Transactions (London) 43 (6), pp. 1140 - 1145 (2015)
  23. Klamt, S.; Mahadevan, R.: On the feasibility of growth-coupled product synthesis in microbial strains. Metabolic Engineering 30, pp. 166 - 178 (2015)
  24. Mahadevan, R.; Kamp von, A.; Klamt, S.: Genome-scale strain designs based on regulatory minimal cut sets. Bioinformatics 31 (17), pp. 2844 - 2851 (2015)
  25. Michailidou, M.; Melas, I.; Messinis, D.; Klamt, S.; Alexopoulos, L.; Kolisis, F.; Loutrari, H.: Network-Based Analysis of Nutraceuticals in Human Hepatocellular Carcinomas Reveals Mechanisms of Chemopreventive Action. CPT: Pharmacometrics & Systems Pharmacology 4 (6), pp. 350 - 361 (2015)
  26. Mueller, S.; Huard, J.; Waldow, K.; Huang, X.; D'Alessandro, L.; Bohl, S.; Börner, K.; Grimm, D.; Klamt, S.; Klingmüller, U. et al.; Schilling, M.: T160‐phosphorylated CDK2 defines threshold for HGF‐dependent proliferation in primary hepatocytes. Molecular Systems Biology 11, 795 (2015)
  27. Straube, R.: Analysis of Substrate Competition in Regulatory Network Motifs: Stimulus-Response Curves, Thresholds and Ultrasensitivity. Journal of Theoretical Biology 380, pp. 74 - 82 (2015)
  28. Thiele, S.; Cerone, L.; Saez-Rodriguez, J.; Siegel, A.; Guciolowski, C.; Klamt, S.: Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies. BMC Bioinformatics 16 (1), 345 (2015)
  29. Wiechert, W.; Klamt, S.: Computational Systems Biology — neues Fach in den Lebenswissenschaften. Biospektrum 21 (1), pp. 46 - 48 (2015)
  30. 2014
    Carius, L.; Rumschinski, P.; Faulwasser, T.; Flockerzi, D.; Grammel, H.; Findeisen, R.: Model-based derivation, analysis and control of unstable microaerobic steady-states-Considering Rhodospirillum rubrum as an example. Biotechnology and Bioengineering 111 (4), pp. 734 - 747 (2014)
  31. Conradi, C.; Mincheva, M.: Catalytic constants enable the emergence of bistability in dual phosphorylation. Interface: Journal of the Royal Society 6 (11), 95, pp. 1742 - 5662 (2014)
  32. Ederer, M.; Steinsiek, S.; Stagge, S.; Rolfe, M. D.; TerBeek, A.; Knies, D.; Teixeira de Mattos, M. J.; Sauter , T.; Green , J.; Poole, R. K. et al.; Bettenbrock, K.; Sawodny, O.: A mathematical model of metabolism and regulation provides a systems-level view of how Escherichia coli responds to oxygen. Frontiers in Microbiology 5, 124, p. 124 (2014)
  33. Erdrich, P.; Knoop, H.; Steuer, R.; Klamt, S.: Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microbial Cell Factories 13, p. 128 - 128 (2014)
  34. Flockerzi, D.; Holstein, K.; Conradi, C.: N-site Phosphorylation Systems with 2N-1 Steady States. Bulletin of Mathematical Biology 76 (8), pp. 1892 - 1916 (2014)
  35. Henkel, S.; Beek, A. T.; Steinsiek, S.; Stagge, S.; Bettenbrock, K.; M. Joost Teixeira de Mattos, M.; Sawodny, O.; Ederer, M.; Sauter, T.: Basic Regulatory Principles of Escherichia coli's Electron Transport Chain for Varying Oxygen Conditions. PLoS One 9 (9), p. e107640 (2014)
  36. Kamp von, A.; Klamt, S.: Enumeration of Smallest Intervention Strategies in Genome-Scale Metabolic Networks. PLoS Computational Biology 10 (1), e1003378 (2014)
  37. Lohr, V.; Hädicke, O.; Genzel, Y.; Jordan, I.; Buentemeyer, H.; Klamt, S.; Reichl, U.: The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis. BMC Biotechnology 14, p. 72 (2014)
  38. Prigent, S.; Collet, G.; Dittami, S. M.; Delage, L.; Ethis de Corny, F.; Dameron, O.; Eveillard, D.; Thiele, S.; Cambefort, J.; Siegel, A. et al.; Tonon, T.: The genome-scale metabolic network of Ectocarpus siliculosus (EctoGEM): a resource to study brown algal physiology and beyond. The Plant Journal 80 (2), pp. 367 - 381 (2014)
  39. Ryll, A.; Bucher, J.; Bonin, A.; Bongard, S.; Gonçalves , E.; Saez- Roidriguez, J.; Niklas, J.; Klamt, S.: A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models. Biosystems 124, pp. 26 - 38 (2014)
  40. Steinsiek, S.; Stagge, S.; Bettenbrock, K.: Analysis of Escherichia coli Mutants with a Linear Respiratory Chain. PLoS One 9 (1), p. e87307 (2014)
  41. Straube, R.: Reciprocal Regulation as a Source of Ultrasensitivity in Two-Component Systems with a Bifunctional Sensor Kinase. PLoS Computational Biology 10 (5), p. e1003614 (2014)
  42. 2013
    Carius, L.; Hädicke, O.; Grammel, H.: Stepwise reduction of the culture redox potential allows the analysis of microaerobic metabolism and photosynthetic membrane synthesis in Rhodospirillum rubrum. Biotechnology and Bioengineering 110 (2), pp. 573 - 585 (2013)
  43. Carius, L.; Carius, A. B.; McIntosh, M.; Grammel, H.: Quorum sensing influences growth and photosynthetic membrane production in high-cell-density cultivations of Rhodospirillum rubrum. BMC Microbiology 13, p. 189 (2013)
  44. Chaoiya, C.; Berenguier, D.; Keating, S. M.; Naldi, A.; van Iersel, M. P.; Rodriguez, N.; Dräger, A.; Büchel, F.; Cokelaer, T.; Kowal, B. et al.; Wicks, B.; Gonçalves, E.; Dorier, J.; Page, M.; Monteiro, P. T.; Kamp von, A.; Xenarius , I.; de Jong, H.; Hucka, M.; Klamt, S.; Thieffrey, D.; Le Novère, N.; Saez-Rodriguez, J.; Helikar, T.: SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formlisms and tools. BMC Systems Biology 7, p. 135 (2013)
  45. Flassig, R.; Heise, S.; Sundmacher, K.; Klamt, S.: An effective framework for reconstructing gene regulatory networks from genetical genomics data. Bioinformatics 29 (2), pp. 246 - 254 (2013)
  46. Gonçalves, E.; Bucher, J.; Ryll, A.; Niklas, J.; Mauch, K.; Klamt, S.; Rocha, M.; Saez-Rodriguez, J.: Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models. Molecular BioSystems 9 (7), pp. 1576 - 1583 (2013)
  47. Gruchattka, E.; Hädicke, O.; Klamt, S.; Schuetz, V.; Kayser , O.: In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories. Microbial Cell Factories 12, 84 (2013)
  48. Holstein, K.; Flockerzi, D.; Conradi, C.: Multistationarity in Sequential Distributed Multisite Phosphorylation Networks. Bulletin of mathematical biology 75 (11), pp. 2028 - 2058 (2013)
  49. Hädicke, O.; Lohr, V.; Genzel, Y.; Reichl, U.; Klamt, S.: Evaluating differences of metabolic performances: Statistical methods and their application to animal cell cultivations. Biotechnology and Bioengineering 110 (10), pp. 2633 - 2642 (2013)
  50. Jahn, S.; Haverkorn van Rijsevijk, B. R.; Sauer, U.; Bettenbrock, K.: A role for EIIANtr in controlling fluxes in the central metabolism of E. coli K12. Biochimica et Biophysica Acta-Molecular Cell Research 1833 (12), pp. 2879 - 2889 (2013)
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