Efficient parallel statistical model checking of biochemical networks

Electronic Proceedings in Theoretical Computer Science, EPTCS

Volumn 14, Issue , 2009, Pages 47-61

  Ballarini, P ^a   Forlin, M ^a   Mazza, T ^a   Prandi, D ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED SOFTWARE ENGINEERING; MODEL CHECKING; SAMPLING; SOFTWARE PROTOTYPING; STOCHASTIC SYSTEMS; TEMPORAL LOGIC;

BEHAVIORAL PROPERTIES; COMPUTATIONAL DEMANDS; CONFIDENCE INTERVAL ESTIMATION; ON-THE FLY VERIFICATION; PROBABILISTIC VERIFICATION; STATISTICAL MODEL CHECKING; STATISTICAL VERIFICATION; STOCHASTIC SIMULATION ALGORITHMS;

STOCHASTIC MODELS;

EID: 85029365544     PISSN: 20752180     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.4204/EPTCS.14.4     Document Type: Conference Paper

References (33)

1. Adnan Aziz, Kumud Sanwal, Vigyan Singhal & Robert Brayton (2000): Model-checking continuous-time Markov chains. ACM Transactions on Computational Logic Vol. 1, pp. pp. 162-170.
2. Christel Baier, Boudewijn Haverkort, Holger Hermann & Joost-Pieter Katoen (2003): Model-Checking Algorithms for Continuous-Time Markov Chains. IEEE Trans. on Software Eng. Vol. 29(6), pp. pp. 524-541.
3. P. Ballarini, R. Guido, T. Mazza & D. Prandi (2009): Taming the complexity of biological pathways through parallel computing. Briefings in Bioinformatics 10(3), pp. 278-288.
4. P. Ballarini, T. Mazza, A. Palmisano & A. Csikasz-Nagy (2009): Studying irreversible transitions in a model of cell cycle regulation. Electronic Notes in Theoretical Computer Science 232, pp. 39-53.
5. Jiří Barnat, Luboš Brim, Ivana Černá, Sven Dražan, Jana Fabriková, Jan Lańík, David Šafrańek & Hongwu Ma (2009): BioDiVinE: A Framework for Parallel Analysis of Biological Models. EPTCS 6(arXiv:0910.0928), pp. 31-45.
6. Lawrence D. Brown, T. Tony Cai & Anirban Dasgupta (2001): Interval Estimation for a Binomial Proportion. Statistical Science 16, pp. 101-133.
7. Lawrence D. Brown, T. Tony Cai & Anirban DasGupta (2002): Confidence Intervals for a binomial proportion and asymptotic expansions. Annals of Statistics 30(1), pp. 160-201.
8. Laurence Calzone, Nathalie Chabrier-Rivier, Francois Fages & Sylvian Soliman (2006): Machine Learning Biochemical Networks from Temporal Logic Properties. In: Transactions on Computational Systems Biology, Lecture Notes in Computer Science. Springer Berlin / Heidelberg, pp. 68-94.
9. Edmund M. Clarke, James R. Faeder, Christopher J. Langmead, Leonard A. Harris, Sumit Kumar Jha & Axel Legay (2008): Statistical Model Checking in BioLab: Applications to the Automated Analysis of T-Cell Re ceptor Signaling Pathway. In: CMSB '08: Proceedings of the 6th International Conference on Computational Methods in Systems Biology. Springer-Verlag, Berlin, Heidelberg, pp. 231-250.
10. Edmund M Clarke, Orna Grumberg & Doron A. Peled (1999): Model Checking. MIT Press.
11. L. Dematte, C. Priami & A. Romanel (2008): The BlenX language: a tutorial. LNCS 5016, p. 313.
12. D. Donaldson, R.;Gilbert (2008): A Monte Carlo Model Checker for Probabilistic LTL with Numerical Constraints. Technical Report, University of Glasgow, Department of Computing Science.
13. François Fages & Aurélien Rizk (2007): On the Analysis of Numerical Data Time Series in Temporal Logic. In: Muffy Calder & Stephen Gilmore, editors: CMSB, Lecture Notes in Computer Science 4695. Springer, pp. 48-63. Available at http://dx.doi.org/10.1007/978-3-540-75140-3-4.
14. D.T. Gillespie (1977): Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 81(25), pp. 2340-2361.
15. D.T. Gillespie (1992): A rigorous derivation of the chemical master equation. Physica A 188(3), pp. 404-425.
16. H. A. Hansson & B. Jonsson (1989): A framework for reasoning about time and reliability. In: Proc. 10th IEEE Real -Time Systems Symposium. IEEE Computer Society Press, Santa Monica, Ca., pp. 102-111.
17. Thomas Hérault, Richard Lassaigne & Sylvain Peyronnet (2006): APMC 3.0: Approximate Verification of Discrete and Continuous Time Markov Chains. In: QEST. IEEE Computer Society, pp. 129-130. Available at http://doi.ieeecomputersociety.org/10.1109/QEST.2006.5.
18. J.-P. Katoen, M. Khattri & I. S. Zapreev (2005): A Markov Reward Model Checker. In: Quantitative Evaluation of Systems (QEST). IEEE Computer Society, Los Alamos, CA, USA, pp. 243-244.
19. H. Kitano (2002): Foundations of Systems Biology. MIT Press.
20. M. Kwiatkowska, G. Norman & D. Parker (2009): PRISM: Probabilistic Model Checking for Performance and Reliability Analysis. ACM SIGMETRICS Performance Evaluation Review 36(4), pp. 40-45.
21. M. Kwiatkowska, G. Norman & D. Parker (2009): Symbolic Systems Biology, chapter Probabilistic Model Checking for Systems Biology. Jones and Bartlett.
22. H. Li, Y. Cao, L.R. Petzold & D.T. Gillespie (2008): Algorithms and software for stochastic simulation of biochemical reacting systems. Biotechnology progress 24(1), p. 56.
23. A. S. Miner & G. Ciardo (1999): Efficient reachability set generation and storage using decision diagrams. In: Proceedings of the 20th Int. Conf. on Applications and Theory of Petri Nets, Lecture Notes in Computer Science 1639. Williamsburg, VA, USA, pp. 6-25.
24. D.O. Morgan (1995): Principles of CDK regulation. Nature (374), pp. 131-134.
25. D.O. Morgan (2006): The Cell Cycle: Principles of Control. New Science Press .
26. B. Novak & J.J. Tyson (2003): Cell Cycle Controls in: C. P . Fall et al., (Eds.), Computational Cell Biology, pp. 261-284. Springer.
27. WalterW. Piegorsch (2004): Sample sizes for improved binomial confidence intervals. Computational Statistics and Data Analysis 46(2), pp. 309 - 316.
28. A. Pnueli (1977): A temporal logic of programs. In: Proc. of the 18th IEEE Symposium Foundations of Computer Science. pp. 46-57.
29. M. Scarpa & A. Bobbio (1998): Kronecker representation of Stochastic Petri nets with discrete PH distributions. In: International Computer Performance and Dependability Symposium - IPDS98. IEEE CS Press, pp. 52-61.
30. William J. Stewart (1994): Introduction to numerical solution of Markov Chains. Princeton.
31. T. Tian & K. Burrage (2005): Parallel Implementation of Stochastic Simulation for Large-scale Cellular Processes. In: Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region. IEEE Computer Society Washington, DC, USA.
32. E. B. Wilson (1927): Probable inference, the law of succession, and statistical inference. Journal of the American Statistical Association 22, pp. 209-212.
33. H. Younes, M. Kwiatkowska, G. Norman & D. Parker (2006): Numerical vs. Statistical Probabilistic Model Checking. International Journal on Software Tools for Technology Transfer (STTT) 8(3), pp. 216-228.