S Vaga et al. (2014) Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast. Mol Syst Biol., 10 (12): 767
A Kowald, E Klipp (2014) Mathematical models of mitochondrial aging and dynamics. Prog Mol Biol Transl Sci., 127: 63-92
M Hilsch et al. (2014) Influenza A matrix protein M1 multimerizes upon binding to lipid membranes. Biophys J., 107 (4): 912-2
C Diener et al. (2014) Yeast mating and image-based quantification of spatial pattern formation. PLoS Comput Biol., 10 (6): e1003690
F Guillaud et al. (2014) Superoxide production by cytochrome bc1 complex: a mathematical model. Biochim Biophys Acta, 1837 (10): 1643-52
M Flöttmann, J Uhlendorf, T Scharp, E Klipp, TW Spiesser (2014) SensA: web-based sensitivity analysis of SBML models. Bioinformatics, 30 (19): 2830-1
M Cvijovic et al. (2014) Bridging the gaps in systems biology. Mol Genet Genomics, 289 (5): 727-34
JG Rodriguez Plaza et al. (2014) Cell penetrating peptides and cationic antibacterial peptides: two sides of the same coin. J Biol Chem., 289 (21): 14448-57
S Kummer et al. (2014) Alteration of protein levels during influenza virus H1N1 infection in host cells: a proteomic survey of host and virus reveals differential dynamics. PLoS One, 9 (4): e94257
R Garcia-Salcedo et al. (2014) Glucose de-repression by yeast AMP-activated protein kinase SNF1 is controlled via at least two independent steps. FEBS J., 281 (7): 1901-17
GM de Hijas-Liste, E Klipp, E Balsa-Canto, JR Banga (2014) Global dynamic optimization approach to predict activation in metabolic pathways. BMC Syst Biol., 8 (1): 1
NJ Stanford et al. (2013) Systematic construction of kinetic models from genome-scale metabolic networks. PLoS One, 8 (11): e79195
M Bock, T Scharp, C Talnikar, E Klipp (2014) BooleSim: an interactive Boolean Network Simulator. Bioinformatics, 30 (1): 131-2
K Tummler, T Lubitz, M Schelker, E Klipp (2013) New types of experimental data shape the use of enzyme kinetics for dynamic network modeling. FEBS J., 281 (2): 549-71
C Linke, E Klipp, H Lehrach, M Barberis, S Krobitsch (2013) Fkh1 and Fkh2 associate with Sir2 to control CLB2 transcription under normal and oxidative stress conditions. Front Physiol., 4: 173
A Supady, E Klipp, M Barberis (2013) A variable fork rate affects timing of origin firing and S phase dynamics in Saccharomyces cerevisiae. J Biotechnol., 168 (2): 174-84
M Flöttmann, F Krause, E Klipp, M Krantz (2013) Reaction-contingency based bipartite Boolean modelling. BMC Syst Biol., 7 (1): 58
E Petelenz-Kurdziel et al. (2013) Quantitative analysis of glycerol accumulation, glycolysis and growth under hyper osmotic stress. PLoS Comput Biol., 9 (6): e1003084
F Krause et al. (2013) biographer: web based editing and rendering of SBGN compliant biochemical networks. Bioinformatics, 29 (11): 1467-8
JA Wodke et al. (2013) Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling. Mol Syst Biol., 9: 653
F Rubelt et al. (2012) Onset of immune senescence defined by unbiased pyrosequencing of human immunoglobulin mRNA repertoires. PLoS One, 7 (11): e49774
J Schaber, R Baltanas, A Bush, E Klipp, A Colman-Lerner (2012) Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast. Mol Syst Biol., 8: 622
TW Spiesser, C Müller, G Schreiber, M Krantz, E Klipp (2012) Size homeostasis can be intrinsic to growing cell populations and explained without size sensing or signalling. FEBS J, 279 (22): 4213-30
MD Leach, E Klipp, LE Cowen, AJ Brown (2012) Fungal Hsp90: a biological transistor that tunes cellular outputs to thermal inputs. Nat Rev Microbiol., 10 (10): 693-704
M Hoffman-Sommer, A Supady, E Klipp (2012) Cell-to-cell communication circuits: Quantitative analysis of synthetic logic gates. Front Physiol., 3: 287
M Flöttmann, T Scharp, E Klipp (2012) A stochastic model of epigenetic dynamics in somatic cell reprogramming. Front Physiol., 3: 216
CF Tiger, F Krause, G Cedersund, R Palmér, E Klipp, S Hohmann, H Kitano, M Krantz (2012) A framework for mapping, visualisation and automatic model creation of signal-transduction networks. Mol Syst Biol., 8: 578
A Kowald, A Hamann, S Zintel, S Ullrich, E Klipp, HD Osiewacz (2012) A systems biological analysis links ROS metabolism to mitochondrial protein quality control. Mech Ageing Dev., 133 (5): 331-7
MD Leach, KM Tyc, AJ Brown, E Klipp (2012) Modelling the regulation of thermal adaptation in Candida albicans, a major fungal pathogen of humans. PLoS One., 7 (3): e32467
P Nicolas et al. (2012) Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis. Science, 335 (6072): 1103-6
JM Buescher et al. (2012) Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism. Science, 335 (6072): 1099-103
M Schulz, E Klipp, W Liebermeister (2012) Propagating semantic information in biochemical network models. Bioinformatics, 13 (1): 18
T Handorf, E Klipp (2011) Modeling mechanistic biological networks: An advanced Boolean approach. Bioinformatics, 28 (4): 557-63
C Kühn, E Klipp (2012) Zooming in on yeast osmoadaptation. Adv Exp Med Biol., 736: 293-310
G Schreiber, M Barberis, S Scolari, C Klaus, A Herrmann, E Klipp (2011) Unraveling interactions of cell cycle-regulating proteins Sic1 and B-type cyclins in living yeast cells: a FLIM-FRET approach. FASEB J., 26 (2): 546-54
M Barberis et al. (2011) Sic1 plays a role in timing and oscillatory behaviour of B-type cyclins. Biotechnol Adv., 30 (1): 108-30
Book chapter M Schulz and E Klipp (2010) Introduction to systems biology in Systems Biology in Psychiatric Research: From High-Throughput Data to Mathematical Modeling (eds F Tretter, PJ Gebicke-Haerter, ER Mendoza, G Winterer) Wiley-VCH Verlag, Weinheim, Germany
MA Adrover et al. (2011) Time-dependent quantitative multicomponent control of the G1-S network by the stress-activated protein kinase Hog1 upon osmostress. Sci Signal., 4 (192): ra63
E Klipp (2011) Computational yeast systems biology: a case study for the MAP kinase cascade. Methods Mol Biol., 759: 323-43
C Waltermann, E Klipp (2011) Information theory based approaches to cellular signaling. Biochim Biophys Acta., 1810 (10): 924-32
M Schulz, F Krause, N Le Novère, E Klipp, W Liebermeister (2011) Retrieval, alignment, and clustering of computational models based on semantic annotations. Mol Syst Biol., 7: 512
M Barberis, C Beck, A Amoussouvi, G Schreiber, C Diener, A Herrmann, E Klipp (2011) A low number of SIC1 miRNA molecules ensures a low noise level in cell cycle progression of budding yeast. Mol Biosyst., 7 (10): 2804-12
Z Zi, Z Feng, DA Chapnick, M Dahl, D Deng, E Klipp, A Moustakas, X Liu (2011) Quantitative analysis of transient and sustained transforming growth factor-β signaling dynamics. Mol Syst Biol., 7: 492
D Waltemath et al. (2011) Minimum information about a simulation experiment (MIASE). PLoS Comput Biol., 7 (4): e1001122
S Stoma, M Fröhlich, S Gerber, E Klipp (2011) STSE: Spatio-temporal simulation environment dedicated to biology. BMC Bioinformatics, 12 (1): 126
J Schaber, M Flöttman, J Li, CF Tiger, S Hohmann, E Klipp (2011) Automated ensemble modeling with modelMaGe: analyzing feedback mechanisms in the Sho1 branch of the HOG pathway. PLoS One, 6 (3): e14791
T Lubitz, M Schulz, E Klipp, W Liebermeister (2010) Parameter balancing in kinetic models of cell metabolism. J Phys Chem B.114(49):16298-303
M Barberis, TW Spiesser, E Klipp (2010) Replication origins and timing of temporal replication in budding yeast: how to solve the conundrum? Curr Genomics, 11(3):199-211
J Schaber, E Klipp (2010) Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks. Curr Opin Biotechnol.22 (1):109-16
C Walternmann, E Klipp (2010) Signal integration in budding yeast. Biochem Soc Trans.38(5):1257-64
J Schaber, MA Adrover, et al. (2010) Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation. Eur Biophys J, 39(11):1547-56
E Klipp, RC Wade, U Kummer (2010) Biochemical network-based drug-target prediction. Curr Opin Biotechnol., 21(4):511-6
F Podo, L Buydens et al. (2010) Triple-negative breast cancer: Present challenges and new perspectives. Mol Oncol., 4(3):209-29
TW Spiesser, C Diener, M Barberis, E Klipp (2010) What influences DNA replication rate in budding yeast? PLoS One, 5(4):e10203
W Liebermeister, J Uhlendorf, E Klipp (2010) Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation. Bioinformatics, 26(12):1528-34
Liebermeister W, Uhlendorf J, Klipp E. Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation. Bioinformatics. 2010 Jun 15;26(12):1528-34
Zi Z, Liebermeister W, Klipp E. A quantitative study of the Hog1 MAPK response to fluctuating osmotic stress in Saccharomyces cerevisiae. PLoS One. 2010 Mar 4;5(3):e9522
Krause F, Uhlendorf J, Lubitz T, Schulz M, Klipp E, Liebermeister W. Annotation and merging of SBML models with semanticSBML. Bioinformatics. 2010 Feb 1;26(3):421-2. Epub 2009 Nov 17. PubMed PMID: 19933161.
Kühn C, Prasad KV, Klipp E, Gennemark P. Formal representation of the high osmolarity glycerol pathway in yeast. Genome Inform. 2010 Jan;22:69-83
Gerber S, Hasenbrink G, Hendriksen W, Van Heusden P, Ludwig J, Klipp E, Lichtenberg-Frate H. Graphical analysis and experimental evaluation of Saccharomyces cerevisiae PTRK1|2 and PBMH1|2 promoter region. Genome Inform. 2010 Jan;22:11-20
Klipp E. Timing matters. FEBS Lett. 2009 Dec 17;583(24):4013-8
Schulz M, Bakker BM, Klipp E. TIde: a software for the systematic scanning of drug targets in kinetic network models. BMC Bioinformatics. 2009 Oct 19;10:344.
Alfieri R, Barberis M, Chiaradonna F, Gaglio D, Milanesi L, Vanoni M, Klipp E, Alberghina L. Towards a systems biology approach to mammalian cell cycle: modeling the entrance into S phase of quiescent fibroblasts after serum stimulation. BMC Bioinformatics. 2009 Oct 15;10 Suppl 12:S16
Kühn C, Wierling C, Kühn A, Klipp E, Panopoulou G, Lehrach H, Poustka AJ. Monte Carlo analysis of an ODE Model of the Sea Urchin Endomesoderm Network. BMC Syst Biol. 2009 Aug 23;3:83
Spiesser TW, Klipp E, Barberis M. A model for the spatiotemporal organization of DNA replication in Saccharomyces cerevisiae. Mol Genet Genomics. 2009 Jul;282(1):25-35
Schaber J, Liebermeister W, Klipp E. Nested uncertainties in biochemical models. IET Syst Biol. 2009 Jan;3(1):1-9
Krantz M, Ahmadpour D, Ottosson LG, Warringer J, Waltermann C, Nordlander B, Klipp E, Blomberg A, Hohmann S, Kitano H. Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal-transduction pathway. Mol Syst Biol. 2009;5:281. Epub 2009 Jun 16
Erjavec N, Cvijovic M, Klipp E, Nyström T. Selective benefits of damage partitioning in unicellular systems and its effects on aging. Proc Natl Acad Sci U S A. 2008 Dec 2;105(48):18764-9
Herrgard MJ, Swainston N, Dobson P, Dunn WB, Arga KY, Arvas M, Blüthgen N, Borger S, Costenoble R, Heinemann M, Hucka M, Le Novere N, Li P, Liebermeister W, Mo ML, Oliveira AP, Petranovic D, Pettifer S, Simeonidis E, Smallbone K, Spasic I, Weichart D, Brent R, Broomhead DS, Westerhoff HV, Kirdar B, Penttilä M, Klipp E, Palsson BO, Sauer U, Oliver SG, Mendes P, Nielsen J, Kell DB. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol. 2008 Oct;26(10):1155-60
Zi Z, Zheng Y, Rundell AE, Klipp E. SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool. BMC Bioinformatics. 2008 Aug 15;9:342
Gerber S, Assmus H, Bakker B, Klipp E. Drug-efficacy depends on the inhibitor type and the target position in a metabolic network--a systematic study. J Theor Biol. 2008 Jun 7;252(3):442-55
Schaber J, Klipp E. Short-term volume and turgor regulation in yeast. Essays Biochem. 2008;45:147-59. Review
Cvijovic M, Soueidan H, Sherman DJ, Klipp E, Nikolski M. Exploratory simulation of cell ageing using hierarchical models. Genome Inform. 2008;21:114-25
Kühn C, Petelenz E, Nordlander B, Schaber J, Hohmann S, Klipp E. Exploring the impact of osmoadaptation on glycolysis using time-varying response-coefficients. Genome Inform. 2008;20:77-90
Flöttmann M, Schaber J, Hoops S, Klipp E, Mendes P. ModelMage: a tool for automatic model generation, selection and management. Genome Inform. 2008;20:52-63
Bruck J, Liebermeister W, Klipp E. Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis. Genome Inform. 2008;20:1-14
Ralser M, Wamelink MM, Kowald A, Gerisch B, Heeren G, Struys EA, Klipp E, Jakobs C, Breitenbach M, Lehrach H, Krobitsch S. Dynamic rerouting of the carbohydrate flux is key to counteracting oxidative stress. J Biol. 2007 Dec 21;6(4):10
Borger S, Liebermeister W, Uhlendorf J, Klipp E. Automatically generated model of a metabolic network. Genome Inform. 2007;18:215-24
Zi Z, Klipp E. Steady state analysis of signal response in receptor trafficking networks. Genome Inform. 2007;18:100-8
Barberis M, Klipp E. Insights into the network controlling the G1/S transition in budding yeast. Genome Inform. 2007;18:85-99
Kühn C, Kühn A, Poustka AJ, Klipp E. Modeling development: spikes of the sea urchin. Genome Inform. 2007;18:75-84
Zi, Z. & Klipp, E. (2007) Constraint-Based Modeling and Kinetic Analysis of the Smad Dependent TGF-\u03b2 Signaling Pathway. PLoS ONE, 2(9):e936
Klipp, E. (2007) Modeling dynamic processes in yeast. Review. Yeast. DOI: 10.1002/yea.1544
Klipp E, Liebermeister W, Helbig A, Kowald A & Schaber J. (2007) Systems Biology standards \u2013 the community speaks. Nature Biotechnology, 25(4), 390-391.
Barberis M, Klipp E, Vanoni M & Alberghina A. (2007). Cell Size at S Phase Initiation: an Emergent Property of the G1/S Network. PLoS Comp. Biol., 3(4), e64.
Zi Z and Klipp E. (2006). SBML-PET: A Systems Biology Markup Language based Parameter Estimation Tool. Bioinformatics, 22(21), 2704-2705.
Klipp E and Liebermeister W. (2006). Mathematical modeling of intracellular signaling pathways. BMC Neuroscience.7
Le Novère N., Finney A., Hucka M., Bhalla U., Campagne F., Collado-Vides J., Crampin E., Halstead M., Klipp E., Mendes P., Nielsen P., Sauro H., Shapiro B., Snoep J.L., Spence H.D., Wanner B.L. (2005) Minimum Information Requested In the Annotation of biochemical Models (MIRIAM) Nature Biotechnology, 23(12), 1509-1515.
Schaber J, et al. (2005). Putative gene expression levels influence amino acid usage and evolutionary rates in endosymbiontic bacteria. Gene352:109-117
Kowald A, Lehrach H & Klipp E. (2005) Alternative Pathways as Mechanism for the Negative Effects Associated with Overexpression of Superoxide Dismutase Journal Theoretical Biology, 238(4):828-40.
Klipp E, Krüger R, Nordlander B, Gennemark P & Hohmann S. (2004). The dynamic response of yeast cells to osmotic shock - a systems biology approach. (submitted)
Schmeier, S., Hakenberg, J., Kowald, A., Klipp, E. & Leser, U. (2003). Text Mining for Systems Biology Using Statistical Learning Methods. Proceedings der Workshop-Woche "Lehren - Lernen - Wissen - Adaptivität (LLWA 2003)", Oktober 2003, Karlsruhe
Liebermeister, W., Klipp, E., Schuster, S. & Heinrich, R. (2003). A theory of optimal differential gene expression. BioSystems (in press).
Klipp, E., Heinrich, R. & Holzhütter, H.-G. (2002). Prediction of temporal gene expression. Metabolic optimisation by redistribution of enzyme activities. Eur. J. Biochem.269 1-8
Bakker, B.M., Assmus, H.E., Bruggeman, F., Haanstra, J.R., Klipp, E. & Westerhoff, H. (2002). Network-based selectivity of antiparasitic inhibitors. Mol. Biol. Rep.29(1-2), 1-5.
Klipp, E. & Heinrich, R. (1999). Competition for enzymes in metabolic pathways. BioSystems54, 1-14.
Heinrich, R., Montero, F., Klipp, E., Waddell, T.G. & Meléndez-Hevia, E. (1997). Theoretical approaches to the evolutionary optimization of glycolysis. Thermodynamic and kinetic constraints. Eur.J.Biochem.243, 191-201
Heinrich, R. & Klipp, E. (1996). Control analysis of unbranched enzymatic chains in states of maximal activity. J. Theor. Biol.182, 243-252
Klipp, E. and Heinrich, R. (1994). Evolutionary optimization of enzyme kinetic parameters; effect of constraints. J. Theor. Biol.171, 309-323
Wilhelm, T, Hoffmann-Klipp, E. and Heinrich, R. (1994). An evolutionary approach to enzyme kinetics; optimization of ordered mechanisms. Bull. Math. Biol.56, 65-106