1. R. Alfieri, E. Bartocci, E. Merelli & L. Milanesi (2011): Modeling the cell cycle: From deterministic models to hybrid systems. Biosystems 105, pp. 34–40, doi:10.1016/j.biosystems.2011.03.002.
  2. V. Baldazzi, P.T. Monteiro, M. Page, D. Ropers, J. Geiselmann & H. Jong (2011): Qualitative Analysis of Genetic Regulatory Networks in Bacteria. Understanding the Dynamics of Biological Systems, pp. 111–130, doi:10.1007/978-1-4419-7964-3_6.
  3. G. Batt, H. De Jong, M. Page & J. Geiselmann (2008): Symbolic reachability analysis of genetic regulatory networks using discrete abstractions. Automatica 44(4), pp. 982–989, doi:10.1016/j.automatica.2007.08.004.
  4. L. Bortolussi & A. Policriti (2011): (Hybrid) automata and (stochastic) programs. The hybrid automata lattice of a stochastic program. Journal of Logic and Computation, doi:10.1093/logcom/exr045.
  5. A. Crudu, A. Debussche, A. Muller & O. Radulescu (to appear, Arxiv preprint arXiv:1101.1431): Convergence of stochastic gene networks to hybrid piecewise deterministic processes. Annals of Applied Probability.
  6. A. Crudu, A. Debussche & O. Radulescu (2009): Hybrid stochastic simplifications for multiscale gene networks. BMC Systems Biology 3(1), pp. 89, doi:10.1186/1752-0509-3-89.
  7. R. David & H. Alla (2008): Discrete, continuous, and hybrid Petri nets. IEEE Control Systems 28, pp. 81–84, doi:10.1109/MCS.2008.920445.
  8. S. Drulhe, G. Ferrari-Trecate & H. de Jong (2008): The switching threshold reconstruction problem for piecewise-affine models of genetic regulatory networks. IEEE Transactions on Automatic Control 53, pp. 153–165, doi:10.1109/TAC.2007.911326.
  9. A.F. Filippov & FM Arscott (1988): Differential equations with discontinuous righthand sides 18. Springer.
  10. AN Gorban & O. Radulescu (2008): Dynamic and static limitation in reaction networks, revisited. In: David West Guy B. Marin & Gregory S. Yablonsky: Advances in Chemical Engineering - Mathematics in Chemical Kinetics and Engineering, Advances in Chemical Engineering 34. Elsevier, pp. 103–173, doi:10.1016/S0065-2377(08)00002-1.
  11. D. Henry (1981): Geometric theory of semilinear parabolic problems. Lecture Notes in Mathematics 840.
  12. P. Lincoln & A. Tiwari (2004): Symbolic systems biology: Hybrid modeling and analysis of biological networks. Hybrid Systems: Computation and Control, pp. 147–165, doi:10.1007/978-3-540-24743-2_44.
  13. A.S. Matveev & A.V. Savkin (2000): Qualitative theory of hybrid dynamical systems. Birkhauser.
  14. B. Mishra (2009): Intelligently deciphering unintelligible designs: algorithmic algebraic model checking in systems biology. Journal of The Royal Society Interface 6(36), pp. 575–597, doi:10.1098/rsif.2008.0546.
  15. V. Noel, D. Grigoriev, S. Vakulenko & O. Radulescu (2012): Tropical geometries and dynamics of biochemical networks. Application to hybrid cell cycle models. Electronic Notes in Theoretical Computer Science 284, pp. 75–91, doi:10.1016/j.entcs.2012.05.016.
  16. V. Noel, S. Vakulenko & O. Radulescu (2010): Piecewise smooth hybrid systems as models for networks in molecular biology. In: Proceedings of JOBIM 2010. Jobim, Montpellier.
  17. V. Noel, S. Vakulenko & O. Radulescu (2011): Algorithm for identification of piecewise smooth hybrid systems: application to eukaryotic cell cycle regulation. Lecture Notes in Computer Science 6833, pp. 225–236, doi:10.1007/978-3-642-23038-7_20.
  18. R. Porreca, S. Drulhe, H. Jong & G. Ferrari-Trecate (2008): Structural identification of piecewise-linear models of genetic regulatory networks. Journal of Computational Biology 15(10), pp. 1365–1380, doi:10.1089/cmb.2008.0109.
  19. O. Radulescu, A. Muller & A. Crudu (2007): Théorèmes limites pour des processus de Markov à sauts. Synthèse des resultats et applications en biologie moleculaire. Technique et Science Informatique 26, pp. 443–469, doi:10.3166/tsi.26.443-469.
  20. D. Ropers, V. Baldazzi & H. de Jong (2011): Model reduction using piecewise-linear approximations preserves dynamic properties of the carbon starvation response in Escherichia coli. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8(1), pp. 166–181, doi:10.1109/TCBB.2009.49.
  21. M.A. Savageau, P.M.B.M. Coelho, R.A. Fasani, D.A. Tolla & A. Salvador (2009): Phenotypes and tolerances in the design space of biochemical systems. Proceedings of the National Academy of Sciences 106(16), pp. 6435, doi:10.1073/pnas.0809869106.
  22. R. Shorten, F. Wirth, O. Mason, K. Wulff & C. King (2007): Stability Criteria for Switched and Hybrid Systems.. SIAM Review 49(4), pp. 545–592, doi:10.1137/05063516X.
  23. A. Singh & J.P. Hespanha (2010): Stochastic hybrid systems for studying biochemical processes. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368(1930), pp. 4995–5011, doi:10.1098/rsta.2010.0211.
  24. R. Singhania, R.M. Sramkoski, J.W. Jacobberger & J.J. Tyson (2011): A hybrid model of mammalian cell cycle regulation. PLoS computational biology 7(2), pp. e1001077, doi:10.1371/journal.pcbi.1001077.
  25. Y. Takeuchi (1996): Global dynamical properties of Lotka-Volterra systems. World Scientific, Singapore.
  26. L. Tavernini (1987): Differential automata and their discrete simulators.. Nonlinear Anal. Theory Methods Applic. 11(6), pp. 665–683, doi:10.1016/0362-546X(87)90034-4.
  27. J.J. Tyson (1991): Modeling the cell division cycle: cdc2 and cyclin interactions. Proceedings of the National Academy of Sciences of the United States of America 88(16), pp. 7328, doi:10.1073/pnas.88.16.7328.
  28. P. Ye, E. Entcheva, SA Smolka & R. Grosu (2008): Modelling excitable cells using cycle-linear hybrid automata. Systems Biology, IET 2(1), pp. 24–32, doi:10.1049/iet-syb:20070001.

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