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Peer-reviewed publications


 

This is a list of our scientific publications, published either in journals or as book chapters. In most cases they are linked via PubMed with their abstracts and pdfs. Names of group members are highlighted. Also highlighted are names of former group members, in case we have ongoing working contacts. You may open these lists either separately by year or all together with the buttons on the right side.

 

2018

  1. K Tummler and E Klipp.
    The discrepancy between data for and expectations on metabolic models: How to match experiments and computational efforts to arrive at quantitative predictions?.
    Curr. Opin. Syst. Biol. 8:1–6, 2018.
    URL

2017

  1. A Auconi, A Giansanti and E Klipp.
    Causal influence in linear Langevin networks without feedback.
    Physical Rev. E 95 (4-1):042315, 2017.
    URL

  2. G Del Rio, E Klipp and A Herrmann.
    Using confocal microscopy and computational modeling to investigate the cell-penetrating properties of antimicrobial peptides.
    Methods Mol. Biol. 1548:191–199, 2017.
    URL

  3. M Heiske, T Letellier and E Klipp.
    Comprehensive mathematical model of oxidative phosphorylation valid for physiological and pathological conditions..
    FEBS J. 284 (17):2802–2828, 2017.
    URL

  4. C Linke, A Chasapi, A González-Novo, I Al Sawad, S Tognetti, E Klipp, M Loog, S Krobitsch, F Posas, I Xenarios and M Barberis.
    A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle.
    npj Syst. Biol. Appl. 3:7, 2017.
    URL

  5. U Münzner, T Lubitz, E Klipp and M Krantz.
    Toward genome-scale models of signal transduction networks.
    In J Nielsen and S Hohmann (eds.). Systems Biology. Wiley-VCH, 2017, pages 215–242.
    URL

  6. M Schelker, S Feau, J Du, N Ranu, E Klipp, G MacBeath, B Schoeberl and A Raue.
    Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.
    Nat. Commun. 8:2032, 2017.
    URL

  7. K Stojanovski, T Ferrar, H Benisty, F Uschner, J Delgado, J Jimenez, C Solé, E Nadal, E Klipp, F Posas, L Serrano and C Kiel.
    Interaction dynamics determine signaling and output pathway responses.
    Cell Rep. 19 (1):136–149, 2017.
    URL

  8. J Theobald, X Cheng, A Ghanem, H Gaitantzi, G Song, E Klipp, J Wodke, H Becker, R Mrowka, K Breitkopf-Heinlein, S Dooley and S Wölfl.
    Monitoring cytochrome P450 activity in living hepatocytes by chromogenic substrates in response to drug treatment or during cell maturation.
    Arch. Toxicol., pages Epub ahead of print, 2017.
    URL

2016

  1. L C Barros de Andrade e Sousa, C Kühn, K M Tyc and E Klipp.
    Dosage and dose schedule screening of drug combinations in agent-based models reveals hidden synergies.
    Front. Physiol. 6:398, 2016.
    URL

  2. W-H Chen, V Van Noort, M Lluch-Senar, M L Hennrich, J A H Wodke, E Yus, A Alibés, G Roma, D R Mende, C Pesavento, A Typas, A-C Gavin, L Serrano and P Bork.
    Integration of multi-omics data of a genome-reduced bacterium: prevalence of post-transcriptional regulation and its correlation with protein abundances.
    Nucleic Acids Res. 44 (3):1192–1202, 2016.
    URL

  3. M Cvijovic, T Höfer, J Aćimović, L Alberghina, E Almaas, D Besozzi, A Blomberg, T Bretschneider, M Cascante, O Collin, P De Atauri, C Depner, R Dickinson, M Dobrzynski, C Fleck, J Garcia-Ojalvo, D Gonze, J Hahn, H M Hess, S Hollmann, M Krantz, U Kummer, T Lundh, G Martial, V M Dos Santos, A Mauer-Oberthür, B Regierer, B Skene, E Stalidzans, J Stelling, B Teusink, C T Workman and S Hohmann.
    Strategies for structuring interdisciplinary education in Systems Biology: an European perspective.
    npj Syst. Biol. Appl. 2:16011, 2016.
    URL

  4. D Davidi, E Noor, W Liebermeister, A Bar-Even, A Flamholz, K Tummler, U Barenholz, M Goldenfeld, T Shlomi and R Milo.
    Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements.
    Proc. Natl. Acad. Sci. U.S.A. 113 (12):3401–3406, 2016.
    URL

  5. S Gerber, M Fröhlich, H Lichtenberg-Fraté, S Shabala, L Shabala and E Klipp.
    A thermodynamic model of monovalent cation homeostasis in the yeast Saccharomyces cerevisiae.
    PLoS Comput. Biol. 12 (1):e1004703, 2016.
    URL

  6. B Goldenbogen, W Giese, M Hemmen, J Uhlendorf, A Herrmann and E Klipp.
    Dynamics of cell wall elasticity pattern shapes the cell during yeast mating morphogenesis.
    Open Biol. 6 (9):160136, 2016.
    URL

  7. L Losensky, B Goldenbogen, G Holland, M Laue, A Petran, J Liebscher, H A Scheidt, A Vogel, D Huster, E Klipp and A Arbuzova.
    Micro -and nano-tubules built from loosely and tightly rolled up thin sheets.
    Phys. Chem. Chem. Phys. 18 (2)(2):1292–1301, 2016.
    URL

  8. T Lubitz, J Hahn, F T Bergmann, E Noor, E Klipp and W Liebermeister.
    SBtab: a flexible table format for data exchange in systems biology.
    Bioinformatics 32 (16):2559–2561, 2016.
    URL

  9. J Pauling and E Klipp.
    Computational lipidomics and lipid bioinformatics: filling In the blanks.
    J. Integr. Bioinform. 13 (1):299, 2016.
    URL

  10. M Schelker, C M Mair, F Jolmes, R-W Welke, E Klipp, A Herrmann, M Flöttmann and C Sieben.
    Viral RNA degradation and diffusion act as a bottleneck for the influenza A virus infection efficiency.
    PLoS Comput. Biol. 12 (10):e1005075, 2016.
    URL

  11. V Schützhold, J Hahn, K Tummler and E Klipp.
    Computational modeling of lipid metabolism in yeast.
    Front. Mol. Biosci. 3:57, 2016.
    URL

  12. T Spiesser, C Kühn, M Krantz and E Klipp.
    The MYpop toolbox: putting yeast stress responses in cellular context on single cell and population scales.
    Biotechnol. J. 11 (9):1158–1168, 2016.
    URL

  13. S R Talemi, C-F Tiger, M Andersson, R Babazadeh, N Welkenhuysen, E Klipp, S Hohmann and J Schaber.
    Systems level analysis of the yeast osmo-stat.
    Sci. Rep. 6:30950, 2016.
    URL

  14. K M Tyc, S E Herwald, J A Hogan, J V Pierce, E Klipp and C A Kumamoto.
    The game theory of Candida albicans colonization dynamics reveals host status-responsive gene expression.
    BMC Syst. Biol. 10:20, 2016.
    URL

  15. D Waltemath, J R Karr, F T Bergmann, V Chelliah, M Hucka, M Krantz, W Liebermeister, P Mendes, C J Myers, P Pir, B Alaybeyoglu, N K Araganathan, K Baghalian, A T Bittig, P E Pinto Burke, M Cantarelli, Y H Chew, R S Costa, J Cursons, T Czauderna, A P Goldberg, H F Gómez, J Hahn, T Hameri, D F Hernandez Gardiol, D Kazakiewicz, I Kiselev, V Knight-Schrijver, C Knüpfer, M König, D Lee, A Lloret-Villas, N Mandrik, J K Medley, B Moreau, H Naderi-Meshkin, S K Palaniappan, D Priego-Espinosa, M Scharm, M Sharma, K Smallbone, N J Stanford, J-H Song, T Theile, M Tokic, N Tomar, V Touré, J Uhlendorf, T M Varusai, L H Watanabe, F Wendland, M Wolfien, J T Yurkovich, Y Zhu, A Zardilis, A Zhukova and F Schreiber.
    Toward community standards and software for whole-cell modeling.
    IEEE Trans. Biomed. Eng. 63 (10):2007–2014, 2016.
    URL

2015

  1. X Cheng, E Dimou, H Alborzinia, F Wenke, A Göhring, S Reuter, N Mah, H Fuchs, M A Andrade-Navarro, J Adjaye, S Gul, C Harms, J Utikal, E Klipp, R Mrowka and S Wölfl.
    Identification of 2-[4-[(4-methoxyphenyl)methoxy]-phenyl]acetonitrile and derivatives as potent Oct3/4 inducers.
    J. Med. Chem. 58 (12):4976–4983, 2015.
    URL

  2. W Giese, M Eigel, S Westerheide, C Engwer and E Klipp.
    Influence of cell shape, inhomogeneities and diffusion barriers in cell polarization models.
    Phys. Biol. 12 (6):066014, 2015.
    URL

  3. P Groth, G Reuter and S Thieme.
    Analysis of genomic data in a cloud computing environment.
    In B Wang, R Li and W Perrizo (eds.). Big Data Analytics in Bioinformatics and Healthcare. IGI Global, 2015, pages 186-214.
    URL

  4. M Lluch-Senar, J Delgado, W-H Chen, V Lloréns-Rico, F J O'Reilly, J A H Wodke, E B Unal, E Yus, S Martínez, R J Nichols, T Ferrar, A Vivancos, A Schmeisky, J Stülke, V Van Noort, A-C Gavin, P Bork and L Serrano.
    Defining a minimal cell: essentiality of small ORFs and ncRNAs in a genome-reduced bacterium.
    Mol. Syst. Biol. 11 (1):780, 2015.
    URL

  5. T Lubitz, N Welkenhuysen, S Shashkova, L Bendrioua, S Hohmann, E Klipp and M Krantz.
    Network reconstruction and validation of the Snf1/AMPK pathway in baker's yeast based on a comprehensive literature review.
    npj Syst. Biol. Appl. 1:15007, 2015.
    URL

  6. T Mori, M Flöttmann, M Krantz, T Akutsu and E Klipp.
    Stochastic simulation of Boolean rxncon models: towards quantitative analysis of large signaling networks.
    BMC Syst. Biol. 9:45, 2015.
    URL

  7. A Raue, B Steiert, M Schelker, C Kreutz, T Maiwald, H Hass, J Vanlier, C Tönsing, L Adlung, R Engesser, W Mader, T Heinemann, J Hasenauer, M Schilling, T Höfer, E Klipp, F Theis, U Klingmüller, B Schöberl and J Timmer.
    Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.
    Bioinformatics 31 (21):3558–3560, 2015.
    URL

  8. B Spiesschaert, B Goldenbogen, S Taferner, M Schade, M Mahmoud, E Klipp, N Osterrieder and W Azab.
    Role of gB and pUS3 in equine herpesvirus 1 transfer between peripheral blood mononuclear cells and endothelial cells: a dynamic in vitro model.
    J. Virol. 89 (23):11899–11908, 2015.
    URL

  9. T W Spiesser, C Kühn, M Krantz and E Klipp.
    Bud-localization of CLB2 mRNA can constitute a growth rate dependent daughter sizer.
    PLoS Comput. Biol. 11 (4):e1004223, 2015.
    URL

  10. S F Thieme, J L Vahldiek, K Tummler, F Poch, O H Gemeinhardt, B Hiebl, K S Lehmann, B Hamm and S M Niehues.
    Value or waste: perfusion imaging following radiofrequency ablation –early experience.
    Clin. Hemorheol. Microcirc. 61 (2):323–331, 2015.
    URL

  11. K Tummler, C Kühn and E Klipp.
    Dynamic metabolic models in context: biomass backtracking.
    Integr. Biol. 7 (8):940–951, 2015.
    URL

  12. J A H Wodke, A Alibés, L Cozzuto, A Hermoso, E Yus, M Lluch-Senar, L Serrano and G Roma.
    MyMpn: a database for the systems biology model organism Mycoplasma pneumoniae.
    Nucleic Acids Res. 43 (Database issue):D618–D623, 2015.
    URL

2014

  1. J Ariño, E Aydar, S Drulhe, D Ganser, J Jorrín, M Kahm, F Krause, S Petrezsélyová, L Yenush, O Zimmermannová, G P H Van Heusden, M Kschischo, J Ludwig, C Palmer, J Ramos and H Sychrová.
    Systems biology of monovalent cation homeostasis in yeast: the translucent contribution.
    Adv. Microb. Physiol. 64:1–63, 2014.
    URL

  2. M Bock, T Scharp, C Talnikar and E Klipp.
    BooleSim: an interactive Boolean network simulator.
    Bioinformatics 30 (1):131–132, 2014.
    URL

  3. M Cvijovic, J Almquist, J Hagmar, S Hohmann, H-M Kaltenbach, E Klipp, M Krantz, P Mendes, S Nelander, J Nielsen, A Pagnani, N Przulj, A Raue, J Stelling, S Stoma, F Tobin, J A H Wodke, R Zecchina and M Jirstrand.
    Bridging the gaps in systems biology.
    Mol. Genet. Genomics 289 (5):727–734, 2014.
    URL

  4. G M De Hijas-Liste, E Klipp, E Balsa-Canto and J R Banga.
    Global dynamic optimization approach to predict activation in metabolic pathways.
    BMC Syst. Biol. 8:1, 2014.
    URL

  5. C Diener, G Schreiber, W Giese, G Del Rio, A Schröder and E Klipp.
    Yeast mating and image-based quantification of spatial pattern formation.
    PLoS Comput. Biol. 10 (6):e1003690, 2014.
    URL

  6. M Floettmann, J Uhlendorf, T Scharp, E Klipp and T W Spiesser.
    SensA: web-based sensitivity analysis of SBML models.
    Bioinformatics 30 (19):2830–2831, 2014.
    URL

  7. R García-Salcedo, T Lubitz, G Beltran, K Elbing, Y Tian, S Frey, O Wolkenhauer, M Krantz, E Klipp and S Hohmann.
    Glucose de-repression by yeast AMP-activated protein kinase SNF1 is controlled via at least two independent steps.
    FEBS J. 281 (7):1901–1917, 2014.
    URL

  8. F Guillaud, S Dröse, A Kowald, U Brandt and E Klipp.
    Superoxide production by cytochrome bc1 complex: a mathematical model.
    Biochim. Biophys. Acta 1837 (10):1643–1652, 2014.
    URL

  9. M Hilsch, B Goldenbogen, C Sieben, C T Höfer, J P Rabe, E Klipp, A Herrmann and S Chiantia.
    Influenza A matrix protein M1 multimerizes upon binding to lipid membranes.
    Biophys. J. 107 (4):912–923, 2014.
    URL

  10. D Hosiner, S Gerber, H Lichtenberg-Fraté, W Glaser, C Schüller and E Klipp.
    Impact of acute metal stress in Saccharomyces cerevisiae.
    PLoS ONE 9 (1):e83330, 2014.
    URL

  11. A Kowald and E Klipp.
    Mathematical models of mitochondrial aging and dynamics.
    In H D Osiewacz (ed.). The Mitochonrion in Aging and Disease (Prog. Mol. Biol. Transl. Sci. 127). Elsevier, 2014, pages 63-92.
    URL

  12. S Kummer, M Flöttmann, B Schwanhäusser, C Sieben, M Veit, M Selbach, E Klipp and A Herrmann.
    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, 2014.
    URL

  13. J G Rodriguez Plaza, R Morales-Nava, C Diener, G Schreiber, Z D Gonzalez, M T Lara Ortiz, I Ortega Blake, O Pantoja, R Volkmer, E Klipp, A Herrmann and G Del Rio.
    Cell penetrating peptides and cationic antibacterial peptides: two sides of the same coin.
    J. Biol. Chem. 289 (21):14448–14457, 2014.
    URL

  14. K Tummler, T Lubitz, M Schelker and E Klipp.
    New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.
    FEBS J. 281 (2):549–571, 2014.
    URL

  15. K M Tyc, C Kühn, D Wilson and E Klipp.
    Assessing the advantage of morphological changes in Candida albicans: a game theoretical study.
    Front. Microbiol. 5:41, 2014.
    URL

  16. F Uschner and E Klipp.
    Information processing in the adaptation of Saccharomyces cerevisiae to osmotic stress: an analysis of the phosphorelay system.
    Syst. Synth. Biol. 8 (4):297–306, 2014.
    URL

  17. S Vaga, M Bernardo-Faura, T Cokelaer, A Maiolica, C A Barnes, L C Gillet, B Hegemann, F Van Drogen, H Sharifian, E Klipp, M Peter, J Saez-Rodriguez and R Aebersold.
    Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast.
    Mol. Syst. Biol. 10 (12):767, 2014.
    URL

2013

  1. M Flöttmann, F Krause, E Klipp and M Krantz.
    Reaction-contingency based bipartite Boolean modelling.
    BMC Syst. Biol. 7:58, 2013.
    URL

  2. F Krause, M Schulz, B Ripkens, M Flöttmann, M Krantz, E Klipp and T Handorf.
    Biographer: web-based editing and rendering of SBGN compliant biochemical networks.
    Bioinformatics 29 (11):1467–1468, 2013.
    URL

  3. C Kühn and P Gennemark.
    Modeling yeast osmoadaptation at different levels of resolution.
    J. Bioinform. Comput. Biol. 11 (2):1330001, 2013.
    URL

  4. C Linke, E Klipp, H Lehrach, M Barberis and S Krobitsch.
    Fkh1 and Fkh2 associate with Sir2 to control CLB2 transcription under normal and oxidative stress conditions.
    Front. Physiol. 4:173, 2013.
    URL

  5. T Maier, J Marcos, J A H Wodke, B Paetzold, M Liebeke, R Gutiérrez-Gallego and L Serrano.
    Large-scale metabolome analysis and quantitative integration with genomics and proteomics data in Mycoplasma pneumoniae.
    Mol. Biosyst. 9:1743–1755, 2013.
    URL

  6. E Petelenz-Kurdziel, C Kuehn, B Nordlander, D Klein, K-K Hong, T Jacobson, P Dahl, J Schaber, J Nielsen, S Hohmann and E Klipp.
    Quantitative analysis of glycerol accumulation, glycolysis and growth under hyper osmotic stress.
    PLoS Comput. Biol. 9 (6):e1003084, 2013.
    URL

  7. M Rother, U Münzner, S Thieme and M Krantz.
    Information content and scalability in signal transduction network reconstruction formats.
    Mol. Biosyst. 9 (8):1993–2004, 2013.
    URL

  8. N J Stanford, T Lubitz, K Smallbone, E Klipp, P Mendes and W Liebermeister.
    Systematic construction of kinetic models from genome-scale metabolic networks.
    PLoS ONE 8 (11):e79195, 2013.
    URL

  9. A Supady, E Klipp and M Barberis.
    A variable fork rate affects timing of origin firing and S phase dynamics in Saccharomyces cerevisiae.
    J. Biotechnol. 168 (2):174–184, 2013.
    URL

  10. J A H Wodke, J Puchałka, M Lluch-Senar, J Marcos, E Yus, M Godinho, R Gutiérrez-Gallego, V A P Martins dos Santos, L Serrano, E Klipp and T Maier.
    Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.
    Mol. Syst. Biol. 9:653, 2013.
    URL

2012 and before

  1. R Heinrich, E Hoffmann and H G Holzhütter.
    Calculation of kinetic parameters of a reversible enzymatic reaction in states of maximal activity.
    Biomed. Biochim. Acta 49(8/9):891–902, 1990.
    URL

  2. R Heinrich and E Hoffmann.
    Kinetic parameters of enzymatic reactions in states of maximal activity; an evolutionary approach.
    J. Theor. Biol. 151 (2):249–283, 1991.
    URL

  3. R Heinrich, E Klipp, A Stephani and T Wilhelm.
    Evolutionary optimization of enzyme on the basis of kinetic and thermodynamic principles.
    In E Gnaiger, F N Gellerich and M Wyss (eds.). What is Controlling Life? 50 Years after Erwin Schroedinger's What is Life? (Modern Trends in Biothermokinetics 3). Insbruck University Press, 1994, pages 99-102.

  4. E Klipp and R Heinrich.
    Evolutionary optimization of enzyme kinetic parameters; effect of constraints.
    J. Theor. Biol. 171 (3):309–323, 1994.
    URL

  5. T Wilhelm, E Hoffmann-Klipp and R Heinrich.
    An evolutionary approach to enzyme kinetics: optimization of ordered mechanisms.
    Bull. Math. Biol. 56 (1):65–106, 1994.
    URL

  6. E Klipp.
    Evolutionary optimization of enzyme kinetic parameters.
    J Biol. Syst. 3 (2):363–376, 1995.
    URL

  7. R Heinrich and E Klipp.
    Control analysis of unbranched enzymatic chains in states of maximal activity.
    J. Theor. Biol. 182 (3):243–252, 1996.
    URL

  8. E Klipp.
    Maximization of enzyme activity under consideration of various constraints.
    In D N Ghista (ed.). Biomedical and Life Physics. Vieweg, 1996, pages 71-84.

  9. E Klipp and R Heinrich.
    Kinetic optimization of multienzyme systems.
    In H V Westerhoff, J L Snoep, F E Sluse, J E Wijker and B N Kholodenko (eds.). Biothermokinetics of the Living Cell. Biothermokinetic Press, 1996, pages 210-13.

  10. R Heinrich, F Montero, E Klipp, T G Waddell and E Melendez-Hevia.
    Kinetic and thermodynamic constraints for the structural design of glycolysis.
    Nonlinear Anal. 30 (3):1793–1804, 1997.
    URL

  11. R Heinrich, F Montero, E Klipp, T G Waddell and E Meléndez-Hevia.
    Theoretical approaches to the evolutionary optimization of glycolysis. Thermodynamic and kinetic constraints.
    Eur. J. Biochem. 243 (1/2):191–201, 1997.
    URL

  12. E Klipp.
    Relations between flux control coefficients and enzyme concentrations in states of minimized total amount of enzyme.
    In C Larsson, I L Pahlman and L Gustafsson (eds.). BioThermoKinetics. In the Post Genomic Era. University, Chalmers Reproservice, 1998, pages 27-9.

  13. E Klipp and R Heinrich.
    Competition for enzymes in metabolic pathways: implications for optimal distributions of enzyme concentrations and for the distribution of flux control.
    BioSystems 54 (1/2):1–14, 1999.
    URL

  14. B M Bakker, H E Assmus, F Bruggeman, J R Haanstra, E Klipp and H Westerhoff.
    Network-based selectivity of antiparasitic inhibitors.
    Molecular biology reports 29 (1/2):1–5, 2002.
    URL

  15. E Klipp, R Heinrich and H-G Holzhütter.
    Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities.
    Eur. J. Biochem. 269 (22):5406–5413, 2002.
    URL

  16. M Lachmann, N W Blackstone, D Haig, A Kowald, R E Michod, E Szathmary, J H Werren and L Wolpert.
    Cooperation and conflict in the evolution of genomes, cells, and multicellular organisms.
    In P Hammerstein (ed.). Genetic and Cultural Evolution of Cooperation. MIT Press, 2003, pages 327-56.
    URL

  17. J Hakenberg, S Schmeier, A Kowald, E Klipp and U Leser.
    Finding kinetic parameters using text mining.
    OMICS J. Integrat. Biol. 8 (2):131–152, 2004.
    URL

  18. E Klipp, W Liebermeister and C Wierling.
    Inferring dynamic properties of biochemical reaction networks from structural knowledge.
    Genome Inform. 15 (1):125–137, 2004.
    URL

  19. E Klipp, B Nordlander, B Kofahl and S Hohmann.
    Shutting the MAP off–and on again?.
    Curr. Genomics 5 (8):637-647, 2004.
    URL

  20. B Kofahl and E Klipp.
    Modelling the dynamics of the yeast pheromone pathway.
    Yeast 21 (10):831–850, 2004.
    URL

  21. A Kowald and E Klipp.
    Alternative pathways might mediate toxicity of high concentrations of superoxide dismutase.
    Ann. N. Y. Acad. Sci. 1019:370–374, 2004.
    URL

  22. W Liebermeister, E Klipp, S Schuster and R Heinrich.
    A theory of optimal differential gene expression.
    BioSystems 76 (1/3):261–278, 2004.
    URL

  23. E Klipp and S Hohmann.
    Simulation von Lebensprozessen.
    BIOForum 28 (10):60–61, 2005.

  24. E Klipp, B Nordlander, R Krüger, P Gennemark and S Hohmann.
    Integrative model of the response of yeast to osmotic shock.
    Nat. Biotechnol. 23 (8):975–982, 2005.
    URL

  25. N Le Novère, A Finney, M Hucka, U S Bhalla, F Campagne, J Collado-Vides, E J Crampin, M Halstead, E Klipp, P Mendes, P Nielsen, H Sauro, B Shapiro, J L Snoep, H D Spence and B L Wanner.
    Minimum information requested in the annotation of biochemical models (MIRIAM).
    Nat. Biotechnol. 23 (12):1509–1515, 2005.
    URL

  26. W Liebermeister and E Klipp.
    Biochemical networks with uncertain parameters.
    IEE Proc. Syst. Biol. 152 (3):97–107, 2005.
    URL

  27. W Liebermeister, U Baur and E Klipp.
    Biochemical network models simplified by balanced truncation.
    FEBS J. 272 (16):4034–4043, 2005.
    URL

  28. B Nordlander, E Klipp, B Kofahl and S Hohmann.
    Modelling signalling pathways –a yeast approach.
    In L Alberghina and H V Westerhoff (eds.). Systems Biology. Definitions and Perspectives (Topics Curr. Gen. 13). Springer, 2005, pages 277-302.
    URL

  29. S Borger, W Liebermeister and E Klipp.
    Prediction of enzyme kinetic parameters based on statistical learning.
    Genome Inform. 17 (1):80–87, 2006.
    URL

  30. O Ebenhöh and W Liebermeister.
    Structural analysis of expressed metabolic subnetworks.
    Genome Inform. 17 (1):163–172, 2006.
    URL

  31. E Klipp and W Liebermeister.
    Mathematical modeling of intracellular signaling pathways.
    BMC Neurosci. 7 (Suppl 1):S10, 2006.
    URL

  32. E Klipp and J Schaber.
    Modelling of signal transduction in yeast –Sensitivity and model analysis.
    In M Cánovas, J L Iborra and Arturo Manjón (eds.). Understanding and Exploiting Systems Biology in Bioprocesses and Biomedicine. Fundación CajaMurcia, 2006, pages 15-30.
    URL

  33. A Kowald, H Lehrach and E Klipp.
    Alternative pathways as mechanism for the negative effects associated with overexpression of superoxide dismutase.
    J. Theor. Biol. 238 (4):828–840, 2006.
    URL

  34. W Liebermeister and E Klipp.
    Bringing metabolic networks to life: convenience rate law and thermodynamic constraints.
    Theor. Biol. Med. Model. 3:41, 2006.
    URL

  35. W Liebermeister and E Klipp.
    Bringing metabolic networks to life: integration of kinetic, metabolic, and proteomic data.
    Theor. Biol. Med. Model. 3:42, 2006.
    URL

  36. C Salazar, J Schütze and O Ebenhöh.
    Bioinformatics meets systems biology.
    Genome Biol. 7 (1):303, 2006.
    URL

  37. J Schaber, B Kofahl, A Kowald and E Klipp.
    A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker's yeast.
    FEBS J. 273 (15):3520–3533, 2006.
    URL

  38. M Schulz, J Uhlendorf, E Klipp and W Liebermeister.
    SBMLmerge, a system for combining biochemical network models.
    Genome Inform. 17 (1):62–71, 2006.
    URL

  39. S Schuster, E Klipp and M Marhl.
    The predictive power of molecular network modelling –case studies of predictions with subsequent experimental verification.
    In F Eisenhaber (ed.). Discovering Biomolecular Mechanisms with Computational Biology. Landes Bioscience, Georgetown and Springer, 2006, pages 95-106.
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  40. Z Zi and E Klipp.
    SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.
    Bioinformatics 22 (21):2704–2705, 2006.
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  41. M Barberis and E Klipp.
    Insights into the network controlling the G1/S transition in budding yeast.
    Genome Inform. 18:85–99, 2007.
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  42. M Barberis, E Klipp, M Vanoni and L Alberghina.
    Cell size at S phase initiation: an emergent property of the G1/S network.
    PLoS Comput. Biol. 3 (4):e64, 2007.
    URL

  43. M Barberis, E Klipp, M Vanoni and L Alberghina.
    Modeling of the G(1)/S transition in yeast cell cycle.
    FEBS J. 274 (Suppl. S1):248, 2007.
    URL

  44. S Borger, W Liebermeister, J Uhlendorf and E Klipp.
    Automatically generated model of a metabolic network.
    Genome Inform. 18:215–224, 2007.
    URL

  45. E Klipp.
    Modelling dynamic processes in yeast.
    Yeast 24 (11):943–959, 2007.
    URL

  46. E Klipp.
    Modeling of yeast cell stress response.
    FEBS J. 274 (Suppl. s1):53, 2007.
    URL

  47. E Klipp, W Liebermeister, A Helbig, A Kowald and J Schaber.
    Systems biology standards -the community speaks.
    Nat. Biotechnol. 25 (4):390–391, 2007.
    URL

  48. C Kühn, A Kühn, A J Poustka and E Klipp.
    Modeling development: spikes of the sea urchin.
    Genome Inform. 18:75–84, 2007.
    URL

  49. M Ralser, M M Wamelink, A Kowald, B Gerisch, G Heeren, E A Struys, E Klipp, C Jakobs, M Breitenbach, H Lehrach and S Krobitsch.
    Dynamic rerouting of the carbohydrate flux is key to counteracting oxidative stress.
    J. Biol. 6 (4):10, 2007.
    URL

  50. Z Zi and E Klipp.
    Cellular signaling is potentially regulated by cell density in receptor trafficking networks.
    FEBS Lett. 581 (24):4589–4595, 2007.
    URL

  51. Z Zi and E Klipp.
    Constraint-based modeling and kinetic analysis of the Smad dependent TGF-β signaling pathway.
    PLoS ONE 2 (9):e936, 2007.
    URL

  52. Z Zi and E Klipp.
    Steady state analysis of signal response in receptor trafficking networks.
    Genome Inform. 18:100–108, 2007.
    URL

  53. M Barberis and E Klipp.
    Sic1 can regulate the fundamental events in the budding yeast cell cycle.
    FEBS J. 275 (Suppl. s1):441, 2008.
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  54. G Basler, Z Nikoloski, O Ebenhöh and T Handorf.
    Biosynthetic potentials from species-specific metabolic networks.
    Genome Inform. 20:135–148, 2008.
    URL

  55. J Bruck, W Liebermeister and E Klipp.
    Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis.
    Genome Inform. 20:1–14, 2008.
    URL

  56. M Cvijovic, H Soueidan, D J Sherman, E Klipp and M Nikolski.
    Exploratory simulation of cell ageing using hierarchical models.
    Genome Inform. 21:114–125, 2008.
    URL

  57. N Erjavec, M Cvijovic, E Klipp and T Nyström.
    Selective benefits of damage partitioning in unicellular systems and its effects on aging.
    Proc. Natl. Acad. Sci. USA 105 (48):18764–18769, 2008.
    URL

  58. M Flöttmann, J Schaber, S Hoops, E Klipp and P Mendes.
    ModelMage: a tool for automatic model generation, selection and management.
    Genome Inform. 20:52–63, 2008.
    URL

  59. S Gerber, H Aßmus, B Bakker and E Klipp.
    Drug-efficacy depends on the inhibitor type and the target position in a metabolic network –A systematic study.
    J. Theor. Biol. 252 (3):442–455, 2008.
    URL

  60. T Handorf, N Christian, O Ebenhöh and D Kahn.
    An environmental perspective on metabolism.
    J. Theor. Biol. 252 (3):530–537, 2008.
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  61. M J Herrgård, N Swainston, P Dobson, W B Dunn, K Y Arga, M Arvas, N Blüthgen, S Borger, R Costenoble, M Heinemann, M Hucka, N Le Novère, P Li, W Liebermeister, M L Mo, A P Oliveira, D Petranovic, S Pettifer, E Simeonidis, K Smallbone, I Spasić, D Weichart, R Brent, D S Broomhead, H V Westerhoff, B Kirdar, M Penttilä, E Klipp, B Ø Palsson, U Sauer, S G Oliver, P Mendes, J Nielsen and D B Kell.
    A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology.
    Nat. Biotechnol. 26 (10):1155–1160, 2008.
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  62. E Klipp and J Schaber.
    Modeling the dynamics of stress activated protein kinases (SAPK) in cellular stress response.
    In F Posas and A R Nebreda (eds.). Stress-Activated Protein Kinases (Topics Curr. Gen. 20). Springer, 2008, pages 205–224.
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  63. C Kühn, E Petelenz, B Nordlander, J Schaber, S Hohmann and E Klipp.
    Exploring the impact of osmoadaptation on glycolysis using time-varying response-coefficients.
    Genome Inform. 20:77–90, 2008.
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  64. J Schaber and E Klipp.
    Short-term volume and turgor regulation in yeast.
    Essays Biochem. 45:147–160, 2008.
    URL

  65. Z Zi, Y Zheng, A E Rundell and E Klipp.
    SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.
    BMC Bioinform. 9:342, 2008.
    URL

  66. R Alfieri, M Barberis, F Chiaradonna, D Gaglio, L Milanesi, M Vanoni, E Klipp and L Alberghina.
    Towards a systems biology approach to mammalian cell cycle: modeling the entrance into S phase of quiescent fibroblasts after serum stimulation.
    BMC Bioinform. 10 (Suppl 12):S16, 2009.
    URL

  67. N Christian, P May, S Kempa, T Handorf and O Ebenhöh.
    An integrative approach towards completing genome-scale metabolic networks.
    Mol. BioSyst. 5 (12):1889–1903, 2009.
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  68. O Ebenhöh and T Handorf.
    Functional classification of genome-scale metabolic networks.
    EURASIP J. Bioinform. Syst. Biol. 2009:570456, 2009.
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  69. E Klipp.
    Timing matters.
    FEBS Lett. 583 (24):4013–4018, 2009.
    URL

  70. M Krantz, D Ahmadpour, L-G Ottosson, J Warringer, C Waltermann, B Nordlander, E Klipp, A Blomberg, St Hohmann and H Kitano.
    Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal-transduction pathway.
    Mol. Syst. Biol. 5:281, 2009.
    URL

  71. C Kühn, C Wierling, A Kühn, E Klipp, G Panopoulou, H Lehrach and A J Poustka.
    Monte Carlo analysis of an ODE model of the sea urchin endomesoderm network.
    BMC Syst. Biol. 3:83, 2009.
    URL

  72. J Schaber, W Liebermeister and E Klipp.
    Nested uncertainties in biochemical models.
    IET Syst. Biol. 3 (1):1–9, 2009.
    URL

  73. M Schulz, B M Bakker and E Klipp.
    TIde: a software for the systematic scanning of drug targets in kinetic network models.
    BMC Bioinform. 10:344, 2009.
    URL

  74. T W Spiesser, E Klipp and M Barberis.
    A model for the spatiotemporal organization of DNA replication in Saccharomyces cerevisiae.
    Mol. Genet. Genomics 282 (1):25–35, 2009.
    URL

  75. E Yus, T Maier, K Michalodimitrakis, V Noort, T Yamada, W-H Chen, J A H Wodke, M Güell, S Martínez, R Bourgeois, S Kühner, E Raineri, I Letunic, O V Kalinina, M Rode, R Herrmann, R Gutiérrez-Gallego, R B Russell, A-C Gavin, P Bork and L Serrano.
    Impact of genome reduction on bacterial metabolism and its regulation.
    Science 326 (5957):1263–1268, 2009.
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  76. M Barberis, T W Spiesser and E Klipp.
    Replication origins and timing of temporal replication in budding yeast: how to solve the conundrum?.
    Curr. Genomics 11 (3):199–211, 2010.
    URL

  77. S Gerber, G Hasenbrink, W Hendriksen, P Van Heusden, J Ludwig, E Klipp and H Lichtenberg-Fraté.
    Graphical analysis and experimental evaluation of Saccharomyces cerevisiae PTRK1|2 and PBMH1|2 promoter region.
    Genome Inform. 22:11–20, 2010.
    URL

  78. E Klipp, R C Wade and U Kummer.
    Biochemical network-based drug-target prediction.
    Curr. Opin. Biotechnol. 21 (4):511–516, 2010.
    URL

  79. F Krause, J Uhlendorf, T Lubitz, M Schulz, E Klipp and W Liebermeister.
    Annotation and merging of SBML models with semanticSBML.
    Bioinformatics 26 (3):421–422, 2010.
    URL

  80. C Kühn, K V S Prasad, E Klipp and P Gennemark.
    Formal representation of the high osmolarity glycerol pathway in yeast.
    Genome Inform. 22:69–83, 2010.
    URL

  81. W Liebermeister, J Uhlendorf and E Klipp.
    Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation.
    Bioinformatics 26 (12):1528–1534, 2010.
    URL

  82. T Lubitz, M Schulz, E Klipp and W Liebermeister.
    Parameter balancing in kinetic models of cell metabolism.
    J Phys. Chem. B 114 (49):16298–16303, 2010.
    URL

  83. F Podo, L M C Buydens, H Degani, R Hilhorst, E Klipp, I S Gribbestad, S Van Huffel, H W M Van Laarhoven, J Luts, D Monleon, G J Postma, N Schneiderhan-Marra, F Santoro, H Wouters, H G Russnes, T Sørlie, E Tagliabue and A-L Børresen-Dale (for the FEMME Consortium).
    Triple-negative breast cancer: present challenges and new perspectives.
    Mol. Oncol. 4 (3):209–229, 2010.
    URL

  84. J Schaber, M A Adrover, E Eriksson, S Pelet, E Petelenz-Kurdziel, D Klein, F Posas, M Goksör, M Peter, S Hohmann and E Klipp.
    Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation..
    Eur. Biophys. J. 39 (11):1547–1556, 2010.
    URL

  85. Schulz M. and E Klipp.
    Introduction to systems biology.
    In F Tretter, G Winterer, P J Gebicke-Haerter and E R Mendoza (eds.). Systems Biology in Psychiatric Research. From High-Throughput Data to Mathematical Modeling. Wiley-VCH, 2010, pages 81-96.
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  86. J Schütze and J Wolf.
    Spatio-temporal dynamics of glycolysis in cell layers. A mathematical model..
    Biosystems 99:104–108, 2010.
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  87. T W Spiesser, C Diener, M Barberis and E Klipp.
    What influences DNA replication rate in budding yeast?.
    PLoS ONE 5 (4):e10203, 2010.
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  88. S Stoma and E Klipp.
    Spatio-temporal simulation environment: a microscopy image based modelization framework.
    Microsc. Microanal. 16 (Suppl. S2):734–735, 2010.
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  89. C Waltermann and E Klipp.
    Signal integration in budding yeast.
    Biochem. Soc. Trans. 38 (5):1257–1264, 2010.
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  90. K Yizhak, T Benyamini, W Liebermeister, E Ruppin and T Shlomi.
    Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model.
    Bioinformatics 26 (12):i255–i260, 2010.
    URL

  91. Z Zi, W Liebermeister and E Klipp.
    A quantitative study of the Hog1 MAPK response to fluctuating osmotic stress in Saccharomyces cerevisiae.
    PLoS ONE 5 (3):e9522, 2010.
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  92. M À Adrover, Z Zi, A Duch, J Schaber, A González-Novo, J Jimenez, M Nadal-Ribelles, J Clotet, E Klipp and F Posas.
    Time-dependent quantitative multicomponent control of the G₁-S network by the stress-activated protein kinase Hog1 upon osmostress.
    Sci. Signal. 4 (192):ra63, 2011.
    URL

  93. M Barberis, C Beck, A Amoussouvi, G Schreiber, C Diener, A Herrmann and E Klipp.
    A low number of SIC1 mRNA molecules ensures a low noise level in cell cycle progression of budding yeast.
    Mol. Biosyst. 7 (10):2804–2812, 2011.
    URL

  94. P Kahlem, A DiCara, M Durot, J M Hancock, E Klipp, V Schächter, E Segal, I Xenarios, Birney E and L Mendoza.
    Strengths and weaknesses of selected modeling methods used in systems biology.
    In N-S Yang (ed.). Systems and Computational Biology–Bioinformatics and Computational Modeling. InTech Open Access Publisher, 2011, pages 77-98.
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  95. E Klipp.
    Computational yeast systems biology: a case study for the MAP kinase cascade.
    In J I Castrillo and S G Oliver (eds.). Yeast Systems Biology: Methods and Protocols (Meth. Mol. Biol. 759). Humana Press, 2011, pages 323–343.
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  96. A Kowald.
    The glyoxalase system as an example of a cellular maintenance pathway with relevance to aging.
    Aging 3 (1):17–18, 2011.
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  97. A Kowald and T B L Kirkwood.
    Evolution of the mitochondrial fusion-fission cycle and its role in aging.
    Proc. Natl. Acad. Sci. USA 108 (25):10237–10242, 2011.
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  98. A Kowald and S Schmeier.
    Text mining for systems modeling.
    Methods Mol. Biol. 696:305–318, 2011.
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  99. A Kowald and C Wierling.
    Standards, tools, and databases for the analysis of yeast 'omics data.
    Methods Mol. Biol. 759:345–365, 2011.
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  100. N Mah, Y Wang, M-C Liao, A Prigione, J Jozefczuk, B Lichtner, K Wolfrum, M Haltmeier, M Flöttmann, M Schaefer, A Hahn, R Mrowka, E Klipp, M A Andrade-Navarro and J Adjaye.
    Molecular insights into reprogramming-initiation events mediated by the OSKM gene regulatory network.
    PLoS ONE 6 (8):e24351, 2011.
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  101. J Schaber and E Klipp.
    Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks.
    Curr. Opin. Biotechnol. 22 (1):109–116, 2011.
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  102. J Schaber, M Flöttmann, J Li, C-F Tiger, S Hohmann and E Klipp.
    Automated ensemble modeling with modelMaGe: analyzing feedback mechanisms in the Sho1 branch of the HOG pathway.
    PLoS ONE 6 (3):e14791, 2011.
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  103. M Schulz, F Krause, N Le Novère, E Klipp and W Liebermeister.
    Retrieval, alignment, and clustering of computational models based on semantic annotations.
    Mol. Syst. Biol. 7:512, 2011.
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  104. J Schütze, T Mair, M J B Hauser, M Falcke and J Wolf.
    Metabolic synchronization by traveling waves in yeast cell layers.
    Biophys. J. 100 (4):809–813, 2011.
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  105. S Stoma, M Fröhlich, S Gerber and E Klipp.
    STSE: spatio-temporal simulation environment dedicated to biology.
    BMC Bioinform. 12:126, 2011.
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  106. Tyc K M and E Klipp.
    Modeling dissemination of pathogenic fungi within a host: a cartoon for the interactions of two complex systems.
    J. Comp. Sci. Syst. Biol. S1:001, 2011.
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  107. D Waltemath, R Adams, D A Beard, F T Bergmann, U S Bhalla, R Britten, V Chelliah, M T Cooling, J Cooper, E J Crampin, A Garny, S Hoops, M Hucka, P Hunter, E Klipp, C Laibe, A K Miller, I Moraru, D Nickerson, P Nielsen, M Nikolski, S Sahle, H M Sauro, H Schmidt, J L Snoep, D Tolle, O Wolkenhauer and N Le Novère.
    Minimum information about a simulation experiment (MIASE).
    PLoS Comput. Biol. 7 (4):e1001122, 2011.
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  108. C Waltermann and E Klipp.
    Information theory based approaches to cellular signaling.
    Biochim. Biophys. Acta 1810 (10):924–932, 2011.
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  109. Z Zi, Z Feng, D A Chapnick, M Dahl, D Deng, E Klipp, A Moustakas and X Liu.
    Quantitative analysis of transient and sustained transforming growth factor-β signaling dynamics.
    Mol. Syst. Biol. 7:492, 2011.
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  110. M Barberis.
    Molecular systems biology of Sic1 in yeast cell cycle regulation through multiscale modeling.
    Adv. Exp. Med. Biol. 736:135–167, 2012.
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  111. M Barberis.
    Sic1 as a timer of Clb cyclin waves in the yeast cell cycle–design cycle –design principle of not just an inhibitor.
    FEBS J. 279 (18):3386–3410, 2012.
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  112. M Barberis, C Linke, M À Adrover, A González-Novo, H Lehrach, S Krobitsch, F Posas and E Klipp.
    Sic1 plays a role in timing and oscillatory behaviour of B-type cyclins.
    Biotechnol. Adv. 30 (1):108–130, 2012.
    URL

  113. J M Buescher, W Liebermeister, M Jules, M Uhr, J Muntel, E Botella, B Hessling, R J Kleijn, L Le Chat, F Lecointe, U Mäder, P Nicolas, S Piersma, F Rügheimer, D Becher, P Bessieres, E Bidnenko, E L Denham, E Dervyn, K M Devine, G Doherty, S Drulhe, L Felicori, M J Fogg, A Goelzer, A Hansen, C R Harwood, M Hecker, S Hubner, C Hultschig, H Jarmer, E Klipp, A Leduc, P Lewis, F Molina, P Noirot, S Peres, N Pigeonneau, S Pohl, S Rasmussen, B Rinn, M Schaffer, J Schnidder, B Schwikowski, J M Van Dijl, P Veiga, S Walsh, A J Wilkinson, J Stelling, S Aymerich and U Sauer.
    Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism.
    Science 335 (6072):1099–1103, 2012.
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  114. M Floettmann, T Scharp and E Klipp.
    Computational modeling of biochemical processes and cell differentiation.
    In M K Stachowiak and E S Tzanakakis (eds.). Stem Cells. From Mechanisms to Technologies. World Scientific, 2012, pages 3-29.
    URL

  115. M Flöttmann, T Scharp and E Klipp.
    A stochastic model of epigenetic dynamics in somatic cell reprogramming.
    Front. Physiol. 3:216, 2012.
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  116. G Fuellen, J Dengjel, A Hoeflich, J Hoeijemakers, H A Kestler, A Kowald, S Priebe, D Rebholz-Schuhmann, B Schmeck, U Schmitz, A Stolzing, J Sühnel, D Wuttke and J Vera.
    Systems biology and bioinformatics in aging research: a workshop report.
    Rejuvenation Res. 15 (6):631–641, 2012.
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  117. C Geijer, I Pirkov, W Vongsangnak, A Ericsson, J Nielsen, M Krantz and S Hohmann.
    Time course gene expression profiling of yeast spore germination reveals a network of transcription factors orchestrating the global response.
    BMC Genom. 13:554, 2012.
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  118. T Handorf and E Klipp.
    Modeling mechanistic biological networks: an advanced Boolean approach.
    Bioinformatics 28 (4):557–563, 2012.
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  119. M Hoffman-Sommer, A Supady and E Klipp.
    Cell-to-cell communication circuits: quantitative analysis of synthetic logic gates.
    Front. Physiol. 3:287, 2012.
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  120. T B L Kirkwood and A Kowald.
    The free-radical theory of ageing–older, wiser and still alive: modelling positional effects of the primary targets of ROS reveals new support.
    Bioessays 34 (8):692–700, 2012.
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  121. A Kowald, A Hamann, S Zintel, S Ullrich, E Klipp and H D Osiewacz.
    A systems biological analysis links ROS metabolism to mitochondrial protein quality control.
    Mech. Ageing Dev. 133 (5):331–337, 2012.
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  122. C Kühn and E Klipp.
    Zooming in on yeast osmoadaptation.
    Adv. Exp. Med. Biol. 736:293–310, 2012.
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  123. M D Leach, E Klipp, L E Cowen and A J P Brown.
    Fungal Hsp90: a biological transistor that tunes cellular outputs to thermal inputs.
    Nat. Rev. Microbiol. 10 (10):693–704, 2012.
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  124. M D Leach, K M Tyc, A J P Brown and E Klipp.
    Modelling the regulation of thermal adaptation in Candida albicans, a major fungal pathogen of humans.
    PLoS ONE 7 (3):e32467, 2012.
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  125. P Nicolas, U Mäder, E Dervyn, T Rochat, A Leduc, N Pigeonneau, E Bidnenko, E Marchadier, M Hoebeke, S Aymerich, D Becher, P Bisicchia, E Botella, O Delumeau, G Doherty, E L Denham, M J Fogg, V Fromion, A Goelzer, A Hansen, E Härtig, C R Harwood, G Homuth, H Jarmer, M Jules, E Klipp, L Le Chat, F Lecointe, P Lewis, W Liebermeister, A March, R A T Mars, P Nannapaneni, D Noone, S Pohl, B Rinn, F Rügheimer, P K Sappa, F Samson, M Schaffer, B Schwikowski, L Steil, J Stülke, T Wiegert, K M Devine, A J Wilkinson, J M Van Dijl, M Hecker, U Völker, P Bessières and P Noirot.
    Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis.
    Science 335 (6072):1103–1106, 2012.
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  126. F Rubelt, V Sievert, F Knaust, C Diener, T S Lim, K Skriner, E Klipp, R Reinhardt, H Lehrach and Z Konthur.
    Onset of immune senescence defined by unbiased pyrosequencing of human immunoglobulin mRNA repertoires.
    PLoS ONE 7 (11):e49774, 2012.
    URL

  127. J Schaber, R Baltanas, A Bush, E Klipp and A Colman-Lerner.
    Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast.
    Mol. Syst. Biol. 8:622, 2012.
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  128. G Schreiber, M Barberis, S Scolari, C Klaus, A Herrmann and E Klipp.
    Unraveling interactions of cell cycle-regulating proteins Sic1 and B-type cyclins in living yeast cells: a FLIM-FRET approach.
    FASEB J. 26 (2):546–554, 2012.
    URL

  129. M Schulz, E Klipp and W Liebermeister.
    Propagating semantic information in biochemical network models.
    BMC Bioinform. 13:18, 2012.
    URL

  130. T W Spiesser, C Müller, G Schreiber, M Krantz and E Klipp.
    Size homeostasis can be intrinsic to growing cell populations and explained without size sensing or signalling.
    FEBS J. 279 (22):4213–4230, 2012.
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  131. C-F Tiger, F Krause, G Cedersund, R Palmér, E Klipp, S Hohmann, H Kitano and M Krantz.
    A framework for mapping, visualisation and automatic model creation of signal-transduction networks.
    Mol. Syst. Biol. 8:578, 2012.
    URL

  132. M Flöttmann, F Krause, E Klipp and M Krantz.
    Reaction-contingency based bipartite Boolean modelling.
    BMC Syst. Biol. 7:58, 2013.
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  133. F Krause, M Schulz, B Ripkens, M Flöttmann, M Krantz, E Klipp and T Handorf.
    Biographer: web-based editing and rendering of SBGN compliant biochemical networks.
    Bioinformatics 29 (11):1467–1468, 2013.
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  134. C Kühn and P Gennemark.
    Modeling yeast osmoadaptation at different levels of resolution.
    J. Bioinform. Comput. Biol. 11 (2):1330001, 2013.
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  135. C Linke, E Klipp, H Lehrach, M Barberis and S Krobitsch.
    Fkh1 and Fkh2 associate with Sir2 to control CLB2 transcription under normal and oxidative stress conditions.
    Front. Physiol. 4:173, 2013.
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  136. T Maier, J Marcos, J A H Wodke, B Paetzold, M Liebeke, R Gutiérrez-Gallego and L Serrano.
    Large-scale metabolome analysis and quantitative integration with genomics and proteomics data in Mycoplasma pneumoniae.
    Mol. Biosyst. 9:1743–1755, 2013.
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  137. E Petelenz-Kurdziel, C Kuehn, B Nordlander, D Klein, K-K Hong, T Jacobson, P Dahl, J Schaber, J Nielsen, S Hohmann and E Klipp.
    Quantitative analysis of glycerol accumulation, glycolysis and growth under hyper osmotic stress.
    PLoS Comput. Biol. 9 (6):e1003084, 2013.
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  138. M Rother, U Münzner, S Thieme and M Krantz.
    Information content and scalability in signal transduction network reconstruction formats.
    Mol. Biosyst. 9 (8):1993–2004, 2013.
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  139. N J Stanford, T Lubitz, K Smallbone, E Klipp, P Mendes and W Liebermeister.
    Systematic construction of kinetic models from genome-scale metabolic networks.
    PLoS ONE 8 (11):e79195, 2013.
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  140. A Supady, E Klipp and M Barberis.
    A variable fork rate affects timing of origin firing and S phase dynamics in Saccharomyces cerevisiae.
    J. Biotechnol. 168 (2):174–184, 2013.
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  141. J A H Wodke, J Puchałka, M Lluch-Senar, J Marcos, E Yus, M Godinho, R Gutiérrez-Gallego, V A P Martins dos Santos, L Serrano, E Klipp and T Maier.
    Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.
    Mol. Syst. Biol. 9:653, 2013.
    URL