Free Access
Med Sci (Paris)
Volume 25, Number 6-7, Juin-Juillet 2009
Page(s) 601 - 607
Section Dossier Biologie des systèmes
Published online 15 June 2009
  1. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000; 100 : 57–70. [Google Scholar]
  2. De Jong H. Modeling and simulation of genetic regulatory systems: a literature review. J Comput Biol 2002; 9 : 67–103. [Google Scholar]
  3. Kitano H. Cancer as a robust system: implications for anticancer therapy. Nat Rev Cancer 2004; 4 : 227–35. [Google Scholar]
  4. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28 : 27–30. [Google Scholar]
  5. Hucka M, Finney A, Sauro HM, et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 2000; 19 : 524–33. [Google Scholar]
  6. Le Novère N, Bornstein B, Broicher A, et al. Biomodels database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res 2006; 34 : D689–91. [Google Scholar]
  7. Calzone L, Gelay A, Zinovyev A, et al. A comprehensive modular map of molecular interactions in RB/E2F pathway. Mol Syst Biol 2008; 4 : 173. [Google Scholar]
  8. Sherr CJ, McCormick F. The RB and p53 pathways in cancer. Cancer Cell 2002; 2 : 103–12. [Google Scholar]
  9. Kitano H, Funahashi A, Matsuoka Y, Oda K. Using process diagrams for the graphical representation of biological networks. Nat Biotech 2005; 23 : 961–6. [Google Scholar]
  10. Rapaport F, Zinovyev A, Dutreix M, et al. Classification of microarray data using gene networks. BMC Bioinformatics 2007; 8 : 35. [Google Scholar]
  11. Song S, Black MA. Microarray-based gene set analysis: a comparison of current methods. BMC Bioinformatics 2008; 9 : 502. [Google Scholar]
  12. Stransky N, Vallot C, Reyal F, et al. Regional copy number-independent deregulation of transcription in cancer. Nat Genet 2006; 38 : 1386–96. [Google Scholar]
  13. Chen KC, Calzone L, Csikasz-Nagy A, et al. Integrative analysis of cell cycle control in budding yeast. Mol Biol Cell 2004; 15 : 3841–62. [Google Scholar]
  14. Cross FR, Schroeder L, Kruse M, Chen KC. Quantitative characterization of a mitotic cyclin threshold regulating exit from mitosis. Mol Biol Cell 2005; 16 : 2129–38. [Google Scholar]
  15. Zi Z, Klipp E. Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway. Plos One 2007; 2 : e936. [Google Scholar]
  16. Lipniacki T, Kimmel M. Deterministic and stochastic models of NFkappaB pathway. Cardiovasc Toxicol 2007; 7 : 215–34. [Google Scholar]
  17. Kholodenko BN. Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades. Eur J Biochem 2000; 267 : 1583–8. [Google Scholar]
  18. Kholodenko BN, Demin OV, Moehren G, Hoek JB. Quantification of short term signaling by the epidermal growth factor receptor. J Biol Chem 1999; 274 : 30169–81. [Google Scholar]
  19. Fussenegger M, Bailey JE, Varner J. A mathematical model of caspase function in apoptosis. Nat Biotechnol 2000; 18 : 768–74. [Google Scholar]
  20. Bentele M, Lavrik I, Ulrich M, et al. Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis. J Cell Biol 2004; 166 : 839–51. [Google Scholar]
  21. Radulescu O, Gorban AN, Zinovyev A, Lilienbaum A. Robust simplifications of multiscale biochemical networks. BMC Syst Biol 2008; 2 : 86. [Google Scholar]
  22. Aebersold R, et al. Report on EU-USA workshop: how systems biology can advance cancer research. Mol Oncol 2009 (sous presse). [Google Scholar]
  23. Thomas R, Kaufman M. Multistationarity, the basis of cell differentiation and memory. I. Structural conditions of multistationarity and other nontrivial behavior. Chaos 2001; 11 : 165–79. [Google Scholar]
  24. Goldbeter A. A minimal cascade model for the mitotic oscillator involving cyclin and cdc2 kinase. Proc Natl Acad Sci USA 1991; 88 : 9107–11. [Google Scholar]
  25. Novák B, Tyson JJ. Modelling the controls of the eukaryotic cell cycle. Biochem Soc Trans 2003; 31 : 1526–9. [Google Scholar]
  26. Segal E, Friedman N, Koller D, Regev A. A module map showing conditional activity of expression modules in cancer. Nat Genet 2004; 36 : 1090–8. [Google Scholar]
  27. Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005; 102 : 15545–50. [Google Scholar]
  28. Kitano H. Towards a theory of biological robustness. Mol Syst Biol 2007; 3 : 137. [Google Scholar]
  29. Alon U. An introduction to systems biology: design principles of biological circuits. Mathematical and computational biology. London : Chapman and Hall/CRC, 2006. [Google Scholar]
  30. Wagner A. Robustness and evolvability in living systems. Princeton: Princeton University Press, 2005. [Google Scholar]
  31. Harbour JW, Dean DC. the Rb/E2F pathway: expanding roles and emerging paradigms. Genes Dev 2000; 14 : 2393–409. [Google Scholar]
  32. Yao G, Lee TJ, Mori S, et al. A bistable Rb-E2F switch underlies the restriction point. Nat Cell Biol 2008; 10 : 476–82. [Google Scholar]

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