1. SBML website.
  2. P.A. Abrahamsson (2010): Potential benefits of intermittent androgen suppression therapy in the treatment of prostate cancer: a systematic review of literature.. Eur Urol 57, pp. 49–59, doi:10.1016/j.eururo.2009.07.049.
  3. M. Bernardo & R. Gorrieri (1998): A tutorial on EMPA: a theory of concurrent processes with nondeterminism, priorities, probabilities and time. Theoret. Comput. Sci. 202, pp. 1–54, doi:10.1016/S0304-3975(97)00127-8.
  4. Supplementary Material.
  5. L. Bortolussi & A. Policriti (2008): Modeling Biological Systems in Concurrent Constraint Programming. Constraints 13(1), doi:10.1007/s10601-007-9034-8.
  6. L. Bortolussi & A. Policriti (2009): Dynamical systems and stochastic programming — from Ordinary Differential Equations and back. T. Comp. Sys. Bio. XI, pp. 216-267, doi:10.1007/978-3-642-04186-0_11.
  7. L. Bortolussi & A. Policriti (2009): Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration. In: Proc. of CompMod, doi:10.4204/EPTCS.6.5.
  8. L. Bortolussi & A. Policriti (2009): Tales of Spatiality in stochastic Concurrent Constraint Programming. In: Proc. of Bio-Logic.
  9. L. Bortolussi & A. Policriti (2010): Hybrid Dynamics of Stochastic Programs. Theor. Comp. Sc. 411(20), pp. 2052-2077, doi:10.1016/j.tcs.2010.02.008.
  10. M. K. Brawer (2006): Hormonal Therapy for Prostate Cancer. Rev Urol 8, pp. S35–S47.
  11. F. Ciocchetta (2009): Bio-PEPA with Events. T. Comp. Sys. Bio. 11, pp. 45–68, doi:10.1007/978-3-642-04186-0_3.
  12. F. Ciocchetta & J. Hillston (2008): Formal methods for computational systems biology, chapter Process algebras in systems biology, pp. 265–312. Springer-Verlag, doi:10.1007/978-3-540-68894-5_8.
  13. F. Ciocchetta & J. Hillston (2009): Bio-PEPA: A framework for the modelling and analysis of biological systems. Theor. Comp. Sc. 410(33-34), pp. 3065 – 3084, doi:10.1016/j.tcs.2009.02.037.
  14. M.H.A. Davis (1993): Markov Models and Optimization. Chapman & Hall.
  15. M. Ajmone Marsan, G. Balbo, G. Conte, S. Donatelli & G. Franceschinis (1995): Modelling with Generalized Stochastic Petri Nets. Wiley.
  16. D. Gillespie (2000): The chemical Langevin equation. Journal of Chemical Physics 113(1), pp. 297–306, doi:10.1063/1.481811.
  17. D.T. Gillespie (1977): Exact Stochastic Simulation of Coupled Chemical Reactions. J. of Phys. Chem. 81(25), doi:10.1021/j100540a008.
  18. H. Hermanns, U. Herzog & J.P. Katoen (2002): Process algebra for performance evaluation. Theor. Comp. Sci. 274(1-2), pp. 43–87, doi:10.1016/S0304-3975(00)00305-4.
  19. A.M. Ideta, G. Tanaka, T. Takeuchi & K. Aihara (2008): A mathematical model of intermittent androgen suppression for prostate cancer. Nonlinear Science 18, pp. 593–614, doi:10.1007/s00332-008-9031-0.
  20. T. L. Jackson (2004): A mathematical model of prostate tumor growth and androgen-independent relapse. Disc Cont Dyn Sys B 4, pp. 187–201, doi:10.3934/dcdsb.2004.4.187.
  21. S.K. Jha, E.M. Clarke, C.J. Langmead, A. Legay, A. Platzer & P. Zuliani (2009): A Bayesian Approach to Model Checking Biological Systems. In: Proc. of the CMSB, pp. 218–234, doi:10.1007/978-3-642-03845-7_15.
  22. P. Lecca, O. Kahramanogullari, D. Morpurgo, C. Priami & R. Soo (2011): Modelling the tumor shrinkage pharmacodynamics with BlenX. In: Proc. of ICCABS, doi:10.1109/UKSIM.2011.24.
  23. T. Mazza & M. Cavaliere (2009): Cell Cycle and Tumor Growth in Membrane Systems with Peripheral Proteins. Electron. Notes Theor. Comput. Sci. 227, pp. 127–141, doi:10.1016/j.entcs.2008.12.108.
  24. C.J. Mode (2005): Semi-Markov Processes. John Wiley & Sons, Ltd.
  25. J. R. Norris (1997): Markov Chains. Cambridge University Press.
  26. A.R. Rao, H.G. Motiwala & O.M.A. Karim (2008): The discovery of Prostate-Specific Antigen. BJU Int. 101, pp. 5–10, doi:10.1111/j.1464-410X.2007.07138.x.
  27. D. Skulj (2009): Discrete time Markov chains with interval probabilities. Int. J. Approx. Reasoning 50(8), pp. 1314–1329, doi:10.1016/j.ijar.2009.06.007.
  28. G. Tanaka, Y. Hirata, S.L. Goldenberg, N. Bruchovsky & K. Aihara (2010): Mathematical modelling of prostate cancer growth and its application to hormone therapy. Phyl Trans Royal Soc A 368, pp. 5029–5044, doi:10.1098/rsta.2010.0221.
  29. D. J. Wilkinson (2006): Stochastic Modelling for Systems Biology. Chapman & Hall.

Comments and questions to:
For website issues: