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Process Calculi, Systems Biology and Artificial Chemistry

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Abstract

Knowledge about life processes develops through the interplay of theoretical speculation and experimental investigation. Both speculation and experiments present several difficulties that call for the development of faithful and accessible abstract models of the phenomena investigated. Several theories and techniques born in computer science have been proposed for the development of models that rely on solid formal bases and allow virtual experiments to be carried out computationally in silico.

This chapter surveys the basics of process calculi and their applications to the modeling of biological phenomena at a system level. Process calculi were born within the theory of concurrency for describing and proving properties of distributed interacting systems. Their application to biological phenomena relies on an interpretation of systems as made of interacting components exhibiting a computational kind of behavior, “cells as computation.”

The first seminal proposals and the subsequent enhancements for best adapting computer science theories to the domain of biology (with particular reference to chemical, biochemical, and cellular phenomena) are surveyed.

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References

  • Aziz A, Sanwal K, Singhal V, Brayton R (2000) Model checking continuous time Markov chains. ACM Trans Comput Logic 1(1):162–170

    Article  MathSciNet  Google Scholar 

  • Baier C, Haverkort B, Hermanns H, Katoen J-P (2003) Model-checking algorithms for continuous-time Markov chains. IEEE Trans Software Eng 29(6):524–541

    Article  Google Scholar 

  • Bergstra JA, Ponse A, and Smolka SA (2001) Handbook of process algebra. North-Holland, Amsterdam, The Netherlands

    MATH  Google Scholar 

  • Bernardo M, Degano P, Zavattaro G (eds) (2008) Formal methods for computational systems biology. In: SFM 2008: 8th international school on formal methods for the design of computer, communication, and software systems, Bertinoro, Italy, June 2008. Lecture notes in computer science, vol 5016. Springer, Berlin

    MATH  Google Scholar 

  • Bodei C (2009) A control flow analysis for beta-binders with and without static compartments. Theor Comput Sci 410(33–34):3110–3127

    Article  MathSciNet  MATH  Google Scholar 

  • Bracciali A, Brunelli M, Cataldo E, Degano P (2008a) Stochastic models for the in silico simulation of synaptic processes. BMC Bioinform 9(4):S7

    Article  Google Scholar 

  • Bracciali A, Brunelli M, Cataldo E, Degano P (2008b) Synapses as stochastic concurrent systems. Theor Comput Sci 408(1):66–82, 2008

    Article  MathSciNet  MATH  Google Scholar 

  • Bradley J (1999) Towards reliable modelling with stochastic process algebras. PhD thesis, Department of Computer Science, University of Bristol

    Google Scholar 

  • Brodo L, Degano P, Priami C (2007) A stochastic semantics for BioAmbients. In: Proceedings of PaCT, Pereslarl-Zalessky, Russia, September 2007. Lecture notes in computer science, vol 4671. Springer, Heidelberg

    Google Scholar 

  • Busi N, Gorrieri R (2006) On the computational power of Brane calculi. In: Transactions on computational systems biology VI. Lecture notes in computer science, vol 4220. Springer, Heidelberg, pp 16–43

    Chapter  Google Scholar 

  • Calzone L, Fages F, Soliman S (2006) BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge. Bioinformatics 22(14):1805–1807

    Article  Google Scholar 

  • Cardelli L (2009) Artificial biochemistry. In: Condon A, Harel D, Kok JN, Salomaa A, Winfree E (eds) Algorithmic bioprocesses. Springer, New York

    Google Scholar 

  • Cardelli L (2008) On process rate semantics. Theor Comput Sci 391(3):190–215

    Article  MathSciNet  MATH  Google Scholar 

  • Cardelli L (2004) Brane calculi-interactions of biological membranes. In: Danos V, Schachter V (eds) Proceedings of computational methods in systems biology, Paris, France, May 2004. Lecture notes in computer science, vol 3082. Springer, Berlin

    Google Scholar 

  • Cardelli L, Gordon A (1998) Mobile ambients. In: Nivat M (ed) Proceedings of FoSSaCS'98, Lisbon, Portugal, March–April 1998. Lecture notes in computer science, vol 1378. Springer, Berlin, pp 140–155

    Google Scholar 

  • Cardelli L, Zavattaro G (2008) On the computational power of biochemistry. In: Proceedings of algebraic biology, Castle of Hagenberg, Austria, July–August 2008. Lecture notes in computer science, vol 5147. Springer, Berlin

    Google Scholar 

  • Chiarugi D, Curti M, Degano P, Marangoni R (2004) ViCe: a VIrtual CEll. In: Proceedings of 2nd international W/S computational methods in systems biology, Paris, France, May 2004. Lecture notes in computer science, vol 3082. Springer, Berlin

    Google Scholar 

  • Chiarugi D, Degano P, Marangoni R (2007) A computational approach to the functional screening of genomes. PLoS Comput Biol 3(9):1801–1806

    Article  MathSciNet  Google Scholar 

  • Chiarugi D, Degano P, Bert Van Klinken J, Marangoni R (2008) Cells in silico: a holistic approach. In: Formal methods for computational systems biology, Bertinoro, Italy, June 2008. Lecture notes in computer science, vol 5016. Springer, Berlin, pp 366–386

    Chapter  Google Scholar 

  • Ciocchetta F, Hillston J (2006) Bio-PEPA: an extension of the process algebra PEPA for biochemical networks. In: Proceedings of FBTC 2007, Lisbon, Portugal, September 2007. Electr Notes Theor Comput Sci 194(3):101–117

    Google Scholar 

  • Ciocchetta F, Hillston J (2008) Process algebras in systems biology. In: Bernardo M, Degano P, Zavattaro G (eds) SFM 2008: Formal methods for computational systems biology, Bertinoro, Italy, June 2008. Lecture notes in computer science, vol 5016. Springer, Berlin, pp 265–312

    Chapter  Google Scholar 

  • Clarke EM, Emerson EA, Sistla AP (1986) Automatic verification of finite-state concurrent systems using temporal logic specifications. ACM Trans Program Lang Syst 8(2):244–263

    Article  MATH  Google Scholar 

  • Damm W, Harel D (2001) LSCs: breathing life into message sequence charts. Formal Methods Syst Des 19(1):45–80

    Article  MATH  Google Scholar 

  • Danos V, Feret J, Fontana W, Harmer R, Krivine J (2007) Rule-based modelling of cellular signalling. In: Proceedings of CONCUR, Lisbon, Portugal, September 2007. Lecture notes in computer science, vol 4703. Springer, Berlin, pp 17–41

    Google Scholar 

  • Degano P, Prandi D, Priami C, Quaglia P (2006) Beta-binders for biological quantitative experiments. In: Proceedings of QAPL06, Vienna, Austria, April 2006. Electr Notes Theor Comput Sci 164(3): 101–117

    Article  Google Scholar 

  • Dematté L, Prandi D, Priami C, Romanel A (2007) Effective Index: A formal measure of drug effects. In: Proceedings of the 2nd Conference Foundations of Systems Biology in Engineering (FOSBE). Stuttgart, Germany, September 2007, pp 485–490

    Google Scholar 

  • Dematté L, Priami C, Romanel A (2008) The BlenX language: a tutorial. In: Bernardo M, Degano P, Zavattaro G (eds) SFM 2008, Bertinoro, Italy, June 2008. Lecture notes in computer science, vol 5016. Springer, Berlin, pp 313–365

    Google Scholar 

  • Doberkat E-E (2007) Stochastic relations. Chapman & Hall/CRC, Boca Raton, FL

    Book  MATH  Google Scholar 

  • Eker S, Knapp M, Laderoute K, Lincoln P, Meseguer J, Sönmez MK (2002) Pathway logic: symbolic analysis of biological signaling. In: Altman RB, Dunker AK, Hunter L, Lauderdale K, Klein TE (eds) Pacific symposium on biocomputing. Kauai, HI, 3–7 January 2002, pp 400–412

    Google Scholar 

  • Emerson EA, Sistla AP (1983) Deciding branching time logic: a triple exponential decision procedure for CTL*. In: Clarke EM, Kozen D (eds) Proceedings logic of programs, Pittsburgh, PA, June 1983. Lecture notes in computer science, vol 164. Springer, Berlin, pp 176–192

    Google Scholar 

  • Ermentrout B (2002) Simulating, analyzing, and animating dynamical systems. SIAM, Philadelphia, PA

    Book  MATH  Google Scholar 

  • Fages F, Soliman S (2008) Formal cell biology in Biocham. In: Bernardo M, Degano P, Zavattaro G (eds) SFM 2008: Formal methods for computational systems biology, Bertinoro, Italy, June 2008. Lecture notes in computer science, vol 5016. Springer, Berlin, pp 265–312

    Google Scholar 

  • Fell DA (1997) Understanding the control of metabolism. Portland Press, London

    Google Scholar 

  • Fersht A (1999) Structure and mechanism in protein science: a guide to enzyme catalysis and protein folding. Freeman, New York

    Google Scholar 

  • Fontana W, Buss LW (1994) The arrival of the fittest: toward a theory of biological organization. Bull Math Biol 56:1–64

    MATH  Google Scholar 

  • Fraser CM et al. (1995) The minimal gene complement of mycoplasma genitalium. Science 270(1):397–403

    Article  Google Scholar 

  • Gardiner CW (2001) Handbook of stochastic methods for physics, chemistry and the natural sciences. Springer, Berlin

    Google Scholar 

  • Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81:2340–2361

    Article  Google Scholar 

  • Gillespie DT, Petzold LR (2006) Numerical simulation for biochemical kinetics. In: Szallasi Z, Stelling J, Perival V (eds) System modeling in cellular biology, 1st edn. MIT Press, Cambridge, MA, pp 331–354

    Google Scholar 

  • Glass J, Assad-Garcia N, Alperovich N (2006) Essential genes of a minimal bacterium. PNAS 103:425–430

    Article  Google Scholar 

  • Hammes GG, Shimmel PR (1970) In: Boyer PD (ed) The enzymes, vol 2. Academic Press, New York

    Google Scholar 

  • Hillston J (1993) PEPA – performance enhanced process algebra. PhD thesis, University of Edinburgh, Computer Science Department

    Google Scholar 

  • Hillston J (1994) The nature of synchronisation. In: Herzog U, Rettelbach M (eds) Proceedings of 2nd workshop on Process Algebras and Performance Modelling (PAPM'92). Erlangen, Germany, July 1994, pp 51–70

    Google Scholar 

  • Hillston J (2005) Process algebras for quantitative analysis. In: LICS 2005: Proceedings of the 20th annual symposium on logic in computer science, Chicago, IL, USA, June 2005. IEEE Computer Society, Washington DC, pp 239–248

    Google Scholar 

  • Hillston J (1996) A compositional approach to performance modelling. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Hinton A, Kwiatkowska M, Norman G, Parker D (2006) PRISM: a tool for automatic verification of probabilistic systems. In: Hermanns H, Palsberg J (eds) Proceedings 12th international conference on tools and algorithms for the construction and analysis of systems, Vienna, Austria. Lecture notes in computer science, vol 3920. Springer, Heidelberg

    Google Scholar 

  • Hoare CAR (1985) Communicating sequential processes. Prentice-Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  • Ihekwaba A, Larcher R, Mardare R, Priami C (2007) BetaWB – a language for modular representation of biological systems. In: Proceedings of ICSB 2007, Long Beach, CA, October 2007

    Google Scholar 

  • Kitano H (2002) Systems biology: a brief overview. Theor Comput Sci 295(5560):1662–1664

    Google Scholar 

  • Kwiatkowska MZ, Norman G, Parker D (2008) Using probabilistic model checking for systems biology. SIGMETRICS Performance Evaluation Review 35(4):14–21

    Article  Google Scholar 

  • Larry L, Roger B (2005) Automatic generation of cellular reaction networks with moleculizer 1.0. Nat Biotechnol 23:131–136

    Article  Google Scholar 

  • Magnasco MO (1997) Chemical kinetics is Turing universal. Phys Rev Lett 78:1190–1193

    Article  Google Scholar 

  • Miculan M, Bacci G (2006) Modal logics for Brane calculus. In: Priami C (ed) CMSB06: Computational methods in systems biology, Trento, Italy, October 2006. Lecture notes in computer science, vol 4210. Springer, Heidelberg, pp 1–16

    Google Scholar 

  • Milazzo P (2008) Formal modeling in systems biology. An approach from theoretical computer Science. VDM - Verlag Dr. Muller, Saarbrücken, Germany

    Google Scholar 

  • Milner R (1980) A calculus of communicating systems. Lecture notes in computer science, vol 92. Springer, Berlin

    Book  Google Scholar 

  • Milner R (1989) Communication and concurrency. Prentice-Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  • Milner R (1999) Communicating and mobile systems: the π-calculus. Cambridge University Press, Cambridge

    Google Scholar 

  • Milner R, Parrow J, Walker D (1992) A calculus of mobile processes, I-II. Inform Comput 100(1):1–77

    Article  MathSciNet  MATH  Google Scholar 

  • Mushegian AR, Koonin EV (1996) A minimal gene set for cellular life derived by comparison of complete bacterial genome. PNAS 93:10268–10273

    Article  Google Scholar 

  • Nielson F, Riis Nielson H, Schuch-Da-Rosa D, Priami C (2004a) Static analysis for systems biology. In: Proceedings of workshop on systeomatics - dynamic biological systems informatics, Cancun, Mexico, 2004. Computer Science Press, Trinity College Dublin, pp 1–6

    Google Scholar 

  • Nielson HR, Nielson F, Pilegaard H (2004b) Spatial analysis of BioAmbient. In: Proceedings of static analysis symposium, Verona, Italy, August 2004. Lecture notes in computer science, vol 3148. Springer, Berlin, pp 69–83

    Google Scholar 

  • Norris JR (1970) Markov chains. Cambridge University Press, Cambridge, MA

    Google Scholar 

  • Paulson LC (1989) The foundation of a generic theorem prover. J Automated Reasoning 5(3):363–397

    Article  MathSciNet  MATH  Google Scholar 

  • Paun G, Pérez-Jiménez MJ, Salomaa A (2007) Spiking neural P systems: an early survey. Int J Found Comput Sci 18(3):435–455

    Article  MATH  Google Scholar 

  • Phillips A, Cardelli L (2007) Efficient, correct simulation of biological processes in the stochastic pi-calculus. In: Calder M, Gilmore S (eds) Proceedings of computational methods in systems biology, Edinburgh, Scotland, September 2007. Lecture notes in computer science, vol 4695. Springer, Heidelberg, pp 184–199

    Google Scholar 

  • Plotkin GD (2004) A structural approach to operational semantics. J Log Algebr Program 60–61:17–139

    MathSciNet  Google Scholar 

  • Priami C (1995) Stochastic π-calculus. Comput J 36(6):578–589

    Article  Google Scholar 

  • Priami C, Quaglia P (2004) Beta binders for biological interactions. In: Proceedings of CMSB, Paris, France, May 2004. Lecture notes in computer science, vol 3082. Springer, Berlin, pp 20–32

    Google Scholar 

  • Priami C, Regev A, Shapiro E, Silvermann W (2004) Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Theor Comput Sci 325(1):141–167

    Article  Google Scholar 

  • Reddy VN, Mavrouvouniotis ML, Liebman MN (1993) Qualitative analysis of biochemical reduction systems. Comput Biol Med 26(1):9–24

    Article  Google Scholar 

  • Regev A, Shapiro E (2002) Cellular abstractions: cells as computation. Nature 419:343

    Article  Google Scholar 

  • Regev A, Panina E, Silverman W, Cardelli L, Shapiro E (2004) BioAmbients: an abstraction for biological compartments. Theor Comput Sci 325(1):141–167

    Article  MathSciNet  MATH  Google Scholar 

  • Sadot A, Fisher J, Barak D, Admanit Y, Stern MJ, Hubbard EJA, Harel D (2008) Toward verified biological models. IEEE/ACM Trans Comput Biol Bioinform 5(2):223–234

    Article  Google Scholar 

  • Sangiorgi D (2004) Bisimulation: from the origins to today. In: LICS 2004: Proceeding of 19th IEEE symposium on logic in computer science, Turku, Finland, July 2004. IEEE Computer Society, Washington DC, pp 298–302

    Chapter  Google Scholar 

  • Schrödinger E (1946) What is life? Macmillan, New York

    Google Scholar 

  • Segel LA (1987) Modeling dynamic phenomena in molecular and cellular biology. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Sifakis J (1982) A unified approach for studying the properties of transition systems. Theor Comput Sci 18:227–258

    Article  MathSciNet  MATH  Google Scholar 

  • Smith GD (2005) Modeling the stochastic gating of ion channels. In: Fall CP, Marland ES, Wagner JM, Tyson JJ (eds) Computational cell biology, 2nd edn. Springer, New York, pp 285–319

    Google Scholar 

  • Soloveichik D, Cook M, Winfree E, Bruck J (2008) Computation with finite stochastic chemical reaction networks. Nat Comput. doi: 10.1007/s11047-008-9067-y (2008)

    Google Scholar 

  • Van Kampen NG (1992) Stochastic processes in physics and in chemistry. Elsevier, Amsterdam, The Netherlands

    Google Scholar 

  • Voit EO (2000) Computational analysis of biochemical systems – a practical guide for biochemists and molecular biologists. Cambridge University Press, Cambridge

    Google Scholar 

  • Wilkinson DJ (2006) Stochastic modelling for systems biology. Chapman & Hall – CRC Press, London

    MATH  Google Scholar 

  • Wolkenhauer O (2008) Systems biology – Dynamic pathway modelling. Manuscript, available at http://www.sbi.uni-rostock.de/dokumente/t_sb.pdf

  • Zhao J, Ridgway D, Broderick G, Kovalenko A, Ellison M (2008) Extraction of elementary rate constants from global network analysis of E. Coli central metabolism. BMC Syst Biol 2:41

    Article  Google Scholar 

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Acknowledgments

The authors are deeply indebted to Luca Cardelli who kindly gave them permission to reuse here parts of his work, as well as Davide Chiarugi and Roberto Marangoni for joint previous work on VICE. The authors thank Enrico Cataldo for helpful comments and suggestions. The first author wishes to thank all the people at the Microsoft Research—University of Trento Centre for Computational and Systems Biology.

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Degano, P., Bracciali, A. (2012). Process Calculi, Systems Biology and Artificial Chemistry. In: Rozenberg, G., Bäck, T., Kok, J.N. (eds) Handbook of Natural Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92910-9_55

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