Introduction to systems biology

  • Frank J. Bruggeman
  • Jorrit J. Hornberg
  • Fred C. Boogerd
  • Hans V. Westerhoff
Part of the Experientia Supplementum book series (EXS, volume 97)


The developments in the molecular biosciences have made possible a shift to combined molecular and system-level approaches to biological research under the name of Systems Biology. It integrates many types of molecular knowledge, which can best be achieved by the synergistic use of models and experimental data. Many different types of modeling approaches are useful depending on the amount and quality of the molecular data available and the purpose of the model. Analysis of such models and the structure of molecular networks have led to the discovery of principles of cell functioning overarching single species. Two main approaches of systems biology can be distinguished. Top-down systems biology is a method to characterize cells using system-wide data originating from the Omics in combination with modeling. Those models are often phenomenological but serve to discover new insights into the molecular network under study. Bottom-up systems biology does not start with data but with a detailed model of a molecular network on the basis of its molecular properties. In this approach, molecular networks can be quantitatively studied leading to predictive models that can be applied in drug design and optimization of product formation in bioengineering. In this chapter we introduce analysis of molecular network by use of models, the two approaches to systems biology, and we shall discuss a number of examples of recent successes in systems biology.


System Biology Molecular Network Theor Biol Ammonium Assimilation Billiard Ball 


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  1. 1.
    Reed JL, Vo TD, Schilling CH, Palsson BO (2003) An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol 4: R54PubMedCrossRefGoogle Scholar
  2. 2.
    Keseler IM, Collado-Vides J, Gama-Castro S, Ingraham J, Paley S, Paulsen IT, Peralta-Gil M, Karp PD (2005) EcoCyc: a comprehensive database resource for Escherichia coli. Nucleic Acids Res 33: D334–337PubMedCrossRefGoogle Scholar
  3. 3.
    Salgado H, Gama-Castro S, Peralta-Gil M, Diaz-Peredo E, Sanchez-Solano F, Santos-Zavaleta A, Martinez-Flores I, Jimenez-Jacinto V, Bonavides-Martinez C, Segura-Salazar J et al. (2006) RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions. Nucleic Acids Res 34: D394–397PubMedCrossRefGoogle Scholar
  4. 4.
    Stelling J, Klamt S, Bettenbrock K, Schuster S, Gilles ED (2002) Metabolic network structure determines key aspects of functionality and regulation. Nature 420: 190–193PubMedCrossRefGoogle Scholar
  5. 5.
    Forster J, Famili I, Fu P, Palsson BO, Nielsen J (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res 13: 244–253PubMedCrossRefGoogle Scholar
  6. 6.
    Price ND, Reed JL, Palsson BO (2004) Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat Rev Microbiol 2: 886–897PubMedCrossRefGoogle Scholar
  7. 7.
    Bakker BM, Michels PAM, Opperdoes FR, Westerhoff HV (1997) Glycolysis in bloodstream from Trypanosoma brucei can be understood in terms of the kinetics of the glycolytic enzymes. J Biol Chem 272: 3207–3215PubMedCrossRefGoogle Scholar
  8. 8.
    Kholodenko BN, Demin OV, Moehren G, Hoek JB (1999) Quantification of short term signaling by the epidermal growth factor receptor. J Biol Chem 274: 30169–30181PubMedCrossRefGoogle Scholar
  9. 9.
    Rohwer JM, Meadow ND, Roseman S, Westerhoff HV, Postma PW (2000) Understanding glucose transport by the bacterial phosphoenolpyruvate:glycose phosphotransferase system on the basis of kinetic measurements in vitro. J Biol Chem 275: 34909–34921PubMedCrossRefGoogle Scholar
  10. 10.
    Teusink B, Passarge J, Reijenga CA, Esgalhado E, van der Weijden CC, Schepper M, Walsh MC, Bakker BM, van Dam K, Westerhoff HV et al. (2000) Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Eur J Biochem 267: 5313–5329PubMedCrossRefGoogle Scholar
  11. 11.
    Hoefnagel MH, Starrenburg MJ, Martens DE, Hugenholtz J, Kleerebezem M, Van S, II, Bongers R, Westerhoff HV, Snoep JL (2002) Metabolic engineering of lactic acid bacteria, the combined approach: kinetic modelling, metabolic control and experimental analysis. Microbiol 148: 1003–1013Google Scholar
  12. 12.
    Bruggeman FJ, Boogerd FC, Westerhoff HV (2005) The multifarious short-term regulation of ammonium assimilation of Escherichia coli: dissection using an in silico replica. Febs J 272: 1965–1985PubMedCrossRefGoogle Scholar
  13. 13.
    Bakker BM, Mensonides FI, Teusink B, van Hoek P, Michels PA, Westerhoff HV (2000) Compartmentation protects trypanosomes from the dangerous design of glycolysis. Proc Natl Acad Sci USA 97: 2087–2092PubMedCrossRefGoogle Scholar
  14. 14.
    Bruggeman FJ, Hornberg JJ, Bakker BM, Westerhoff HV (2005) Introduction to computational models of biochemical reaction networks. In: A Kriete, R Eils (eds): Computational Systems Biology, ElsevierGoogle Scholar
  15. 15.
    Cascante M, Boros LG, Comin-Anduix B, de Atauri P, Centelles JJ, Lee PW (2002) Metabolic control analysis in drug discovery and disease. Nat Biotechnol 20: 243–249PubMedCrossRefGoogle Scholar
  16. 16.
    Michels PAM, Bakker BM, Opperdoes FR, Westerhoff HV (In press) On the mathematical modelling of metabolic pathways and its use in the identification of the most suitable drug target. In: H Vial, A Fairlamb, R Ridley (eds): Tropical disease guidelines and issues: discoveries and drug development, WHO, Geneva.Google Scholar
  17. 17.
    Tyson JJ, Chen K, Novak B (2001) Network dynamics and cell physiology. Nat Rev Mol Cell Biol 2: 908–916PubMedCrossRefGoogle Scholar
  18. 18.
    Tyson JJ, Chen KC, Novak B (2003) Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr Opin Cell Biol 15: 221–231PubMedCrossRefGoogle Scholar
  19. 19.
    Selkov EE, Reich JG (1981) Energy metabolism of the cell. Academic Press, LondonGoogle Scholar
  20. 20.
    Westerhoff HV, Palsson BO (2004) The evolution of molecular biology into systems biology. Nat Biotechnol 22: 1249–1252PubMedCrossRefGoogle Scholar
  21. 21.
    Alberghina L, Westerhoff HV (eds) (2005) Systems biology: definitions and perspectives (topics in current genetics), Springer-Verlag Berlin, Heidelberg GmbHGoogle Scholar
  22. 22.
    Bruggeman FJ, Westerhoff HV, Boogerd FC (2002) BioComplexity: a pluralist research strategy is necessary for a mechanistic explanation of the “live” state. Philosophical Psychology 15: 411–440CrossRefGoogle Scholar
  23. 23.
    Kauffman SA (1971) Articulation of parts explanations in biology. In: RC Buck, RS Cohen (eds): Boston studies in the philosophy of science. Kluver Academic Publishers, 257–272Google Scholar
  24. 24.
    Machamer P, Darden L, Craver CF (2000) Thinking about mechanisms. Philosophy of Science 67: 1–25CrossRefGoogle Scholar
  25. 25.
    Boogerd FC, Bruggeman FJ, Richardson R, Stephan S (2005) Emergence and its place in nature: A case study of biochemical networks. Synthese 145: 131–164CrossRefGoogle Scholar
  26. 26.
    Darden L, Maull N (1977) Interfield theories. Philosophy of Sci 44: 43–64CrossRefGoogle Scholar
  27. 27.
    Auyang SY (1998) Foundation of complex-system theories: in economics, evolutionary biology, and statistical physics. Cambridge University Press, CambridgeGoogle Scholar
  28. 28.
    Tyson JJ, Novak B, Odell GM, Chen K, Thron CD (1996) Chemical kinetic theory: Understanding cell cycle regulation. Trends Biochem Sci 21: 89–96PubMedCrossRefGoogle Scholar
  29. 29.
    Olivier BG, Snoep JL (2004) Web-based kinetic modelling using JWS Online. Bioinformatics 20: 2143–2144PubMedCrossRefGoogle Scholar
  30. 30.
    Snoep JL, Bruggeman F, Olivier BG, Westerhoff HV (2005) Towards building the silicon cell: A modular approach. Biosystems 83: 207–216PubMedCrossRefGoogle Scholar
  31. 31.
    Cornish-Bowden A (1995) Fundamentals of enzyme kinetics. Portland Press, LondonGoogle Scholar
  32. 32.
    Westerhoff HV, Van Dam K (1987) Thermodynamics and control of biological free-energy transduction. Elsevier Science Publishers BV (Biomedical Division), AmsterdamGoogle Scholar
  33. 33.
    Alberty RA (2002) Thermodynamics of systems of biochemical reactions. J Theor Biol 215: 491–501PubMedCrossRefGoogle Scholar
  34. 34.
    Kacser H, Burns JA (1973) The control of flux. Symp Soc Exp Biol 27: 65–104PubMedGoogle Scholar
  35. 35.
    Heinrich R, Rapoport TA (1974) A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur J Biochem 42: 89–95PubMedCrossRefGoogle Scholar
  36. 36.
    Fell DA (1997) Understanding the control of metabolism, First Edition. Portland Press, London and MiamiGoogle Scholar
  37. 37.
    Westerhoff HV, Chen YD (1984) How do enzyme activities control metabolite concentrations? An additional theorem in the theory of metabolic control. Eur J Biochem 142: 425–430PubMedCrossRefGoogle Scholar
  38. 38.
    Kahn D, Westerhoff HV (1991) Control theory of regulatory cascades. J Theor Biol 153: 255–285PubMedCrossRefGoogle Scholar
  39. 39.
    Hofmeyr JH, Westerhoff HV (2001) Building the cellular puzzle: control in multi-level reaction networks. J Theor Biol 208: 261–285PubMedCrossRefGoogle Scholar
  40. 40.
    Van Kampen NG (1992) Stochastic processes in chemistry and physics. North-Holland, AmsterdamGoogle Scholar
  41. 41.
    Elf J, Ehrenberg M (2003) Fast evaluation of fluctuations in biochemical networks with the linear noise approximation. Genome Res 13: 2475–2484PubMedCrossRefGoogle Scholar
  42. 42.
    Reder C (1988) Metabolic control theory: a structural approach. J Theor Biol 135: 175–201PubMedCrossRefGoogle Scholar
  43. 43.
    Kholodenko BN, Westerhoff HV, Puigjaner J, Cascante M (1995) Control in channeled pathways — a matrix-method calculating the enzyme control coefficients. Biophys Chem 53: 247–258PubMedCrossRefGoogle Scholar
  44. 44.
    Westerhoff HV, Kell DB (1996) What bio technologists knew all along? J Theor Biol 182: 411–420PubMedCrossRefGoogle Scholar
  45. 45.
    Hornberg JJ, Bruggeman FJ, Binder B, Geest CR, de Vaate AJ, Lankelma J, Heinrich R, Westerhoff HV (2005b) Principles behind the multifarious control of signal transduction. ERK phosphorylation and kinase/phosphatase control. Febs J 272: 244–258PubMedCrossRefGoogle Scholar
  46. 46.
    Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95: 14863–14868PubMedCrossRefGoogle Scholar
  47. 47.
    Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 9: 3273–3297PubMedGoogle Scholar
  48. 48.
    Ideker T, Thorsson V, Ranish JA, Christmas R, Buhler J, Eng JK, Bumgarner R, Goodlett DR, Aebersold R, Hood L (2001) Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292: 929–934PubMedCrossRefGoogle Scholar
  49. 49.
    Daran-Lapujade P, Jansen ML, Daran JM, van Gulik W, de Winde JH, Pronk JT (2004) Role of transcriptional regulation in controlling fluxes in central carbon metabolism of Saccharomyces cerevisiae. A chemostat culture study. J Biol Chem 279: 9125–9138PubMedCrossRefGoogle Scholar
  50. 50.
    Ihmels JH, Bergmann S (2004) Challenges and prospects in the analysis of large-scale gene expression data. Brief Bioinform 5: 313–327PubMedCrossRefGoogle Scholar
  51. 51.
    Chassagnole C, Noisommit-Rizzi N, Schmid JW, Mauch K, Reuss M (2002) Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng 79: 53–73CrossRefPubMedGoogle Scholar
  52. 52.
    Lee E, Salic A, Kruger R, Heinrich R, Kirschner MW (2003) The roles of APC and Axin derived from experimental and theoretical analysis of the Wnt pathway. PLoS Biol 1: E10PubMedCrossRefGoogle Scholar
  53. 53.
    Ideker T, Galitski T, Hood L (2001) A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2: 343–372PubMedCrossRefGoogle Scholar
  54. 54.
    Barabasi AL, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5: 101–113PubMedCrossRefGoogle Scholar
  55. 55.
    Albert R, Barabasi AL (2002) Statistical mechanics of complex networks. Revs Mod Physics 74: 47–97CrossRefGoogle Scholar
  56. 56.
    Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45: 167–256CrossRefGoogle Scholar
  57. 57.
    Fell DA, Wagner A (2000) The small world of metabolism. Nat Biotechnol 18: 1121–1122PubMedCrossRefGoogle Scholar
  58. 58.
    Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL (2000) The large-scale organization of metabolic networks. Nature 407: 651–654PubMedCrossRefGoogle Scholar
  59. 59.
    Ravasz E, Somera AL, Mongru DA, Oltvai ZN, Barabasi AL (2002) Hierarchical organization of modularity in metabolic networks. Science 297: 1551–1555PubMedCrossRefGoogle Scholar
  60. 60.
    Tanay A, Sharan R, Kupiec M, Shamir R (2004) Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. Proc Natl Acad Sci USA 101: 2981–2986PubMedCrossRefGoogle Scholar
  61. 61.
    Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U (2002) Network motifs: simple building blocks of complex networks. Science 298: 824–827PubMedCrossRefGoogle Scholar
  62. 62.
    Shen-Orr SS, Milo R, Mangan S, Alon U (2002) Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 31: 64–68PubMedCrossRefGoogle Scholar
  63. 63.
    Yeger-Lotem E, Sattath S, Kashtan N, Itzkovitz S, Milo R, Pinter RY, Alon U, Margalit H (2004) Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction. Proc Natl Acad Sci USA 101: 5934–5939PubMedCrossRefGoogle Scholar
  64. 64.
    Schuster S, Dandekar T, Fell DA (1999) Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol 17: 53–60PubMedCrossRefGoogle Scholar
  65. 65.
    Schilling CH, Letscher D, Palsson BO (2000) Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J Theor Biol 203: 229–248PubMedCrossRefGoogle Scholar
  66. 66.
    Covert MW, Schilling CH, Palsson B (2001) Regulation of gene expression in flux balance models of metabolism. J Theor Biol 213: 73–88PubMedCrossRefGoogle Scholar
  67. 67.
    Papin JA, Stelling J, Price ND, Klamt S, Schuster S, Palsson BO (2004) Comparison of network-based pathway analysis methods. Trends Biotechnol 22: 400–405PubMedCrossRefGoogle Scholar
  68. 68.
    Garfinkel D, Hess B (1964) Metabolic control mechanisms. Vii.A Detailed computer model of the glycolytic pathway in ascites cells. J Biol Chem 239: 971–983PubMedGoogle Scholar
  69. 69.
    Rapoport TA, Heinrich R, Jacobasc G, Rapoport S (1974) Linear steady-state treatment of enzymatic chains — mathematical-model of glycolysis of human erythrocytes. Eur J Biochem 42: 107–120PubMedCrossRefGoogle Scholar
  70. 70.
    Guckenheimer J, Holms P (1983) Nonlinear oscillations, dynamical systems, and bifurcations of vector fields. Springer-Verlag, New YorkGoogle Scholar
  71. 71.
    Nicolis G, Prigogine I (1977) Self-organization in nonequilibrium systems: from dissipative structures to order through fluctuations. John Wiley & Sons, New YorkGoogle Scholar
  72. 72.
    Nicolis G, Prigogine I (1989) Exploring complexity: An introduction. WH Freeman & Co. San FranciscoGoogle Scholar
  73. 73.
    Lefever R, Nicolis G (1971) Chemical instabilities and sustained oscillations. J Theor Biol 30: 267–284PubMedCrossRefGoogle Scholar
  74. 74.
    Goldbeter A, Lefever R (1972) Dissipative structures for an allosteric model — application to glycolytic oscillations. Biophysical J 12: 1302Google Scholar
  75. 75.
    Selkov E (1975) Stabilization of energy charge, generation of oscillations and multiple steady states in energy metabolism as a result of purely stoichiometric regulation. Eur J Biochem 59: 151–157CrossRefGoogle Scholar
  76. 76.
    Goldbeter A (1997) Biochemical oscillations and cellular rhythms: the molecular bases of periodic and chaotic behaviour. Cambridge University Press, CambridgeGoogle Scholar
  77. 77.
    Hynne R, Dano S, Sorensen PG (2001) Full-scale model of glycolysis in Saccharomyces cerevisiae. Biophys Chem 94: 121–163PubMedCrossRefGoogle Scholar
  78. 78.
    Reijenga KA, van Megen YM, Kooi BW, Bakker BM, Snoep JL, van Verseveld HW, Westerhoff HV (2005) Yeast glycolytic oscillations that are not controlled by a single oscillophore: a new definition of oscillophore strength. J Theor Biol 232: 385–398PubMedGoogle Scholar
  79. 79.
    Kremling A, Bettenbrock K, Laube B, Jahreis K, Lengeler JW, Gilles ED (2001) The organization of metabolic reaction networks. III. Application for diauxic growth on glucose and lactose. Metab Eng 3: 362–379PubMedCrossRefGoogle Scholar
  80. 80.
    Teusink B, Walsh MC, van Dam K, Westerhoff HV (1998) The danger of metabolic pathways with turbo design. Trends Biochem Sci 23: 162–169PubMedCrossRefGoogle Scholar
  81. 81.
    Teusink B, Passarge J, Reijenga CA, Esgalhado E, Van der Weijden CC, Schepper M, Walsh MC, Bakker BM, Van Dam K, Westerhoff HV et al. (2000) Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Eur J Biochem 267: 5313–5329PubMedCrossRefGoogle Scholar
  82. 82.
    ter Kuile BH, Westerhoff HV (2001) Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway. FEBS Lett 500: 169–171PubMedCrossRefGoogle Scholar
  83. 83.
    Even S, Lindley ND, Cocaign-Bousquet M (2003) Transcriptional, translational and metabolic regulation of glycolysis in Lactococcus lactis subsp. cremoris MG 1363 grown in continuous acidic cultures. Microbiol 149: 1935–1944CrossRefGoogle Scholar
  84. 84.
    Rossell S, van der Weijden CC, Kruckeberg AL, Bakker BM, Westerhoff HV (2005) Hierarchical and metabolic regulation of glucose influx in starved Saccharomyces cerevisiae. FEMS Yeast Res 5: 611–619PubMedCrossRefGoogle Scholar
  85. 85.
    Rhee SG, Chock PB, Stadtman ER (1989) Regulation of Escherichia coli glutamine synthetase. Adv Enzymol Relat Areas Mol Biol 62: 37–92PubMedCrossRefGoogle Scholar
  86. 86.
    Ninfa AJ, Jiang P, Atkinson MR, Peliska JA (2000) Integration of antagonistic signals in the regulation of nitrogen assimilation in Escherichia coli. Curr Top Cell Regul 36: 31–75PubMedGoogle Scholar
  87. 87.
    Kustu S, Hirschman J, Burton D, Jelesko J, Meeks JC (1984) Covalent modification of bacterial glutamine synthetase: physiological significance. Mol Gen Genet 197: 309–317PubMedCrossRefGoogle Scholar
  88. 88.
    Hoffmann A, Levchenko A, Scott ML, Baltimore D (2002) The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298: 1241–1245PubMedCrossRefGoogle Scholar
  89. 89.
    Schoeberl B, Eichler-Jonsson C, Gilles ED, Muller G (2002) Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Nat Biotechnol 20: 370–375PubMedCrossRefGoogle Scholar
  90. 90.
    Hornberg JJ, Binder B, Bruggeman FJ, Schoeberl B, Heinrich R, Westerhoff HV (2005) Control of MAPK signalling: from complexity to what really matters. Oncogene 24: 5533–5542PubMedCrossRefGoogle Scholar
  91. 91.
    Kruger R, Heinrich R (2004) Model reduction and analysis of robustness for the Wnt/beta-catenin signal transduction pathway. Genome Inform Ser Workshop Genome Inform 15: 138–148Google Scholar
  92. 92.
    Borisov NM, Markevich NI, Hoek JB, Kholodenko BN (2005) Signaling through receptors and scaffolds: independent interactions reduce combinatorial complexity. Biophys J 89: 951–966PubMedCrossRefGoogle Scholar
  93. 93.
    Conzelmann H, Saez-Rodriguez J, Sauter T, Kholodenko BN, Gilles ED (2006) A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks. BMC Bioinformatics 7: 34PubMedCrossRefGoogle Scholar
  94. 94.
    Ferrell JE Jr, Machleder EM (1998) The biochemical basis of an all-or-none cell fate switch in Xenopus oocytes. Science 280: 895–898PubMedCrossRefGoogle Scholar
  95. 95.
    Bagowski CP, Ferrell JE Jr (2001) Bistability in the JNK cascade. Curr Biol 11: 1176–1182PubMedCrossRefGoogle Scholar
  96. 96.
    Brandman O, Ferrell JE Jr, Li R, Meyer T (2005) Interlinked fast and slow positive feedback loops drive reliable cell decisions. Science 310: 496–498PubMedCrossRefGoogle Scholar
  97. 97.
    Pomerening JR, Kim SY, Ferrell JE Jr (2005) Systems-level dissection of the cell-cycle oscillator: bypassing positive feedback produces damped oscillations. Cell 122: 565–578PubMedCrossRefGoogle Scholar
  98. 98.
    Rosenfeld N, Elowitz MB, Alon U (2002) Negative autoregulation speeds the response times of transcription networks. J Mol Biol 323: 785–793PubMedCrossRefGoogle Scholar
  99. 99.
    Mangan S, Alon U (2003) Structure and function of the feed-forward loop network motif. Proc Natl Acad Sci USA 100: 11980–11985PubMedCrossRefGoogle Scholar
  100. 100.
    Mangan S, Zaslaver A, Alon U (2003) The coherent feedforward loop serves as a sign-sensitive delay element in transcription networks. J Mol Biol 334: 197–204PubMedCrossRefGoogle Scholar
  101. 101.
    Dekel E, Mangan S, Alon U (2005) Environmental selection of the feed-forward loop circuit in gene-regulation networks. Phys Biol 2: 81–88PubMedCrossRefGoogle Scholar
  102. 102.
    Mangan S, Itzkovitz S, Zaslaver A, Alon U (2006) The incoherent feed-forward loop accelerates the response-time of the gal system of Escherichia coli. J Mol Biol 356: 1073–1081PubMedCrossRefGoogle Scholar
  103. 103.
    Pomerening JR, Sontag ED, Ferrell JE Jr (2003) Building a cell cycle oscillator: hysteresis and bistability in the activation of Cdc2. Nat Cell Biol 5: 346–351PubMedCrossRefGoogle Scholar
  104. 104.
    Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297: 1183–1186PubMedCrossRefGoogle Scholar
  105. 105.
    Ozbudak EM, Thattai M, Kurtser I, Grossman AD, van Oudenaarden A (2002) Regulation of noise in the expression of a single gene. Nat Genet 31: 69–73PubMedCrossRefGoogle Scholar
  106. 106.
    Swain PS, Elowitz MB, Siggia ED (2002) Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc Natl Acad Sci USA 99: 12795–12800PubMedCrossRefGoogle Scholar
  107. 107.
    Paulsson J (2004) Summing up the noise in gene networks. Nature 427: 415–418PubMedCrossRefGoogle Scholar
  108. 108.
    Thattai M, van Oudenaarden A (2004) Stochastic gene expression in fluctuating environments. Genetics 167: 523–530PubMedCrossRefGoogle Scholar
  109. 109.
    Golding I, Paulsson J, Zawilski SM, Cox EC (2005) Real-time kinetics of gene activity in individual bacteria. Cell 123: 1025–1036PubMedCrossRefGoogle Scholar
  110. 110.
    Pedraza JM, van Oudenaarden A (2005) Noise propagation in gene networks. Science 307: 1965–1969PubMedCrossRefGoogle Scholar
  111. 111.
    Rosenfeld N, Young JW, Alon U, Swain PS, Elowitz MB (2005) Gene regulation at the single-cell level. Science 307: 1962–1965PubMedCrossRefGoogle Scholar
  112. 112.
    Elf J, Paulsson J, Berg OG, Ehrenberg M (2003) Near-critical phenomena in intracellular metabolite pools. Biophys J 84: 154–170PubMedCrossRefGoogle Scholar

Copyright information

© Birkhäuser Verlag/Switzerland 2007

Authors and Affiliations

  • Frank J. Bruggeman
    • 1
    • 2
  • Jorrit J. Hornberg
    • 1
  • Fred C. Boogerd
    • 1
  • Hans V. Westerhoff
    • 1
    • 2
  1. 1.Molecular Cell Physiology, Institute for Molecular Cell Biology, BioCentrum Amsterdam, Faculty of Earth and Life SciencesVrije UniversiteitAmsterdamThe Netherlands
  2. 2.Systems Biology Group, Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, School of Chemical Engineering and Analytical ScienceUniversity of ManchesterManchesterUK

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