Franck van Breugel & James Worrell (2001):
Towards Quantitative Verification of Probabilistic Transition Systems.
In: ICALP,
LNCS 2076.
Springer,
pp. 421–432,
doi:10.1007/3-540-48224-5_35.
Peter Buchholz (1994):
Exact and Ordinary Lumpability in Finite Markov Chains.
Journal of Applied Probability 31(1),
pp. 59–75,
doi:10.2307/3215235.
Peter Buchholz (1994):
Markovian Process Algebra: Composition and Equivalence.
In: Proc. 2nd PAPM Workshop,
Erlangen, Germany.
Luca Cardelli (2008):
On process rate semantics.
Theor. Comput. Sci. 391,
pp. 190–215,
doi:10.1016/j.tcs.2007.11.012.
Federica Ciocchetta & Jane Hillston (2009):
Bio-PEPA: A framework for the modelling and analysis of biological systems.
Theor. Comput. Sci. 410(33–34),
pp. 3065–3084,
doi:10.1016/j.tcs.2009.02.037.
Vincent Danos, Jerome Feret, Walter Fontana, Russell Harmer & Jean Krivine (2010):
Abstracting the Differential Semantics of Rule-Based Models: Exact and Automated Model Reduction.
In: LICS,
pp. 362–381.
Available at http://doi.ieeecomputersociety.org/10.1109/LICS.2010.44.
Vincent Danos & Cosimo Laneve (2004):
Formal molecular biology.
Theoretical Computer Science 325(1),
pp. 69–110,
doi:10.1016/j.tcs.2004.03.065.
Josee Desharnais, Radha Jagadeesan, Vineet Gupta & Prakash Panangaden (2002):
The metric analogue of weak bisimulation for probabilistic processes.
In: LICS,
pp. 413–422,
doi:10.1109/LICS.2002.1029849.
Alessandra Di Pierro, Chris Hankin & Herbert Wiklicky (2003):
Quantitative Relations and Approximate Process Equivalences.
In: CONCUR,
pp. 498–512.
Available at http://dx.doi.org/10.1007/978-3-540-45187-7_33.
James R. Faeder, Michael L. Blinov & William S. Hlavacek (2009):
Rule-Based Modeling of Biochemical Systems with BioNetGen.
Methods Mol. Biol. 500,
pp. 113–167,
doi:10.1007/978-1-59745-525-1_5.
S. Gilmore, J. Hillston & M. Ribaudo (2001):
An efficient algorithm for aggregating PEPA models.
IEEE Transactions on Software Engineering 27(5),
pp. 449–464,
doi:10.1109/32.922715.
Richard A. Hayden, Anton Stefanek & Jeremy T. Bradley (2012):
Fluid computation of passage-time distributions in large Markov models.
Theor. Comput. Sci. 413(1),
pp. 106–141,
doi:10.1016/j.tcs.2011.07.017.
Holger Hermanns & Marina Ribaudo (1998):
Exploiting Symmetries in Stochastic Process Algebras.
In: European Simulation Multiconference,
Manchester, UK,
pp. 763–770.
J. Hillston (2005):
Fluid flow approximation of PEPA models.
In: Proceedings of Quantitative Evaluation of Systems.
IEEE Computer Society Press,
pp. 33–43,
doi:10.1109/QEST.2005.12.
Jane Hillston (1996):
A compositional approach to performance modelling.
Cambridge University Press,
New York, NY, USA,
doi:10.1017/CBO9780511569951.
Giulio Iacobelli & Mirco Tribastone (2013):
Lumpability of fluid models with heterogeneous agent types.
In: DSN,
pp. 1–11,
doi:10.1109/DSN.2013.6575346.
Chi-Chang Jou & Scott Smolka (1990):
Equivalences, congruences, and complete axiomatizations for probabilistic processes.
In: CONCUR,
LNCS 458,
pp. 367–383,
doi:10.1007/BFb0039071.
Ovidiu Radulescu, Alexander N. Gorban, Andrei Zinovyev & Vincent Noel (2012):
Reduction of dynamical biochemical reactions networks in computational biology.
Frontiers in Genetics 3(131),
doi:10.3389/fgene.2012.00131.
Mirco Tribastone, Stephen Gilmore & Jane Hillston (2012):
Scalable Differential Analysis of Process Algebra Models.
IEEE Transactions on Software Engineering 38(1),
pp. 205–219.
Available at http://doi.ieeecomputersociety.org/10.1109/TSE.2010.82.
Pu Wang, Marta C. González, César A. Hidalgo & Albert-László Barabási (2009):
Understanding the Spreading Patterns of Mobile Phone Viruses.
Science 324(5930),
pp. 1071–1076,
doi:10.1126/science.1167053.
Raymond Keith Watson (1972):
On an Epidemic in a Stratified Population.
Journal of Applied Probability 9(3),
pp. 659–666,
doi:10.2307/3212334.