Skip to main content
SpringerLink
Log in

Symbolic Systems Biology: Hybrid Modeling and Analysis of Biological Networks

  • Conference paper
Hybrid Systems: Computation and Control (HSCC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2993))

Included in the following conference series:

Abstract

How do living cells compute and control themselves, and communicate with their environment? We describe the modeling and analysis of dynamic and reactive biological systems involving both discrete and continuous behaviors, to help begin to answer that question. Continuous components arise as differential equations specifying how the concentrations of various molecular species evolve over time. Discrete components of models of biological systems arise from state transitions (eg. from healthy to abnormal states), abstractions and approximations, nonlinear effects, and the presence of inherently discrete processes, often observed in systems governed by one or a few molecules. Once a hybrid model is obtained, analysis techniques such as those described in this and previous HSCC workshops can be usefully applied to help uncover structure in the dynamics of biological systems of interest.

Research supported in part by the National Science Foundation under grant CCR-0311348, DARPA BioSpice contract DE-AC03-765F00098 to Lawrence Berkeley Laboratory, and DARPA BioSpice contract F30602-01-C-0153 to SRI International.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alur, R., Belta, C., Ivancic, F., Kumar, V., Mintz, M., Pappas, G., Rubin, H., Schug, J.: Hybrid modeling and simulation of biological systems. In: Di Benedetto, M.D., Sangiovanni-Vincentelli, A.L. (eds.) HSCC 2001. LNCS, vol. 2034, pp. 19–32. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  2. Bower, J.M., Bolouri, H. (eds.): Computational modeling of genetic and biochemical networks. MIT Press, Cambridge (2001)

    Google Scholar 

  3. Collier, J.R., Monk, A.M., Maini, P.K., Lewis, J.H.: Pattern formation by lateral inhibition with feedback: A mathematical model of Delta-Notch intercellular signalling. J. of theor. Biology 183, 429–446 (1996)

    Article  Google Scholar 

  4. Csete, M.E., Doyle, J.C.: Reverse engineering of biological complexity. Science 295, 1664–1669 (2002)

    Article  Google Scholar 

  5. Dill, D.L., Lincoln, P.: Evolution as design engineer. In: Priami, C. (ed.) CMSB 2003. LNCS, vol. 2602, pp. 202–206. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Eker, S., Knapp, M., Laderoute, K., Lincoln, P., Meseguer, J., Sonmez, K.: Pathway logic: Symbolic analysis of biological signaling. In: Altman, R.B., et al. (eds.) Proceedings of the Pacific Symposium on Biocomputing, January 2002, vol. 7, pp. 400–412 (2002)

    Google Scholar 

  7. Gallivan, M.A., Murray, R.M.: Model reduction and system identification for master equation control systems. In: American Control Conference (2003) (submitted for publication)

    Google Scholar 

  8. Garvey, T.D., Lincoln, P., Pedersen, C.J., Martin, D., Johnson, M.: Biospice: Biospice: Access to the most current computational tools for biologists. OMICS 7(4), 411–420 (2003)

    Article  Google Scholar 

  9. Ghosh, R., Tiwari, A., Tomlin, C.: Automated symbolic reachability analysis with application to delta-notch signaling automata. In: Maler, O., Pnueli, A. (eds.) HSCC 2003. LNCS, vol. 2623, pp. 233–248. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Ghosh, R., Tomlin, C.J.: Lateral inhibition through delta-notch signaling: A piecewise affine hybrid model. In: Di Benedetto, M.D., Sangiovanni-Vincentelli, A.L. (eds.) HSCC 2001. LNCS, vol. 2034, pp. 232–246. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  11. Gillespie, D.T.: A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comp. Physics 22, 403–434 (1976)

    Article  MathSciNet  Google Scholar 

  12. Graf, S., Saïdi, H.: Construction of abstract state graphs with PVS. In: Grumberg, O. (ed.) CAV 1997. LNCS, vol. 1254, pp. 72–83. Springer, Heidelberg (1997)

    Google Scholar 

  13. Guyton, J.R., Foster, R.O., Soeldner, J.S., Tan, M.H., Kahn, C.B., Konez, L., Gleason, R.E.: A model of glucose-insulin homeostasis in man that incorporates the heterogeneous fast pool theory of pancreatic insulin release. Diabetes 27, 1027–1042 (1978)

    Article  Google Scholar 

  14. Hong, H.: Quantifier elimination in elementary algebra and geometry by partial cylindrical algebraic decomposition version 13. In: The world wide web, (1995), http://www.gwdg.de/~cais/systeme/saclib , www.eecis.udel.edu/~saclib/

  15. Hucka, M., Finney, A., Sauro, H.M., Bolouri, H., Doyle, J.C., Kitano, H., Arkin, A.P., et al.: The systems biology markup language (sbml): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4), 524–531 (2003)

    Article  Google Scholar 

  16. Hybridsal: Modeling and abstracting hybrid systems, Computer Science Laboratory, SRI International, Menlo Park, CA (2003), http://www.csl.sri.com/users/tiwari/HybridSalDoc.ps

  17. Ideker, T., Galitski, T., Hood, L.: A new approach to decoding life: Systems biology. Annual Review Genomics – Human Genetics 2, 343–372 (2001)

    Article  Google Scholar 

  18. Karp, P.D.: Pathway databases: A case study in computational symbolic theories. Science 293, 2040–2044 (2001)

    Article  Google Scholar 

  19. Kitano, H.: Systems biology: an overview. Science 295, 1662–1664 (2002)

    Article  Google Scholar 

  20. Kuipers, B.J.: Qualitative reasoning: Modeling and simulation with incomplete knowledge. MIT Press, Cambridge (1994)

    Google Scholar 

  21. Kumar, S.P., Feidler, J.C.: Biospice: A computational infrastructure for integrative biology. OMICS 7(3), 225–226 (2003)

    Article  Google Scholar 

  22. Laub, M., McAdams, H., Feldbluym, T., Fraser, C., Shapiro, L.: Global analysis of the genetic network controlling a bacterial cell cycle. Science 290, 2144–2148 (2000)

    Article  Google Scholar 

  23. Marnellos, G., Deblandre, G.A., Mjolsness, E., Kintner, C.: Delta-Notch lateral inhibitory patterning in the emergence of ciliated cells in xenopus: Experimental observations and a gene network model. Pacific symposium on biocomputing 5, 326–337 (2000)

    Google Scholar 

  24. McAdams, H.H., Arkin, A.: Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. USA 94, 814–819 (1997)

    Article  Google Scholar 

  25. McAdams, H.H., Arkin, A.: It’s a noisy business! genetic regulation at the nanomolar scale. Trends in Genetics 15(2), 65–69 (1999)

    Article  Google Scholar 

  26. Mjolsness, E., Sharp, D.H., Reinitz, J.: A connectionist model of development. J. of theor. Biology 152, 429–453 (1991)

    Article  Google Scholar 

  27. Parker, R.S., Doyle, F.J., Peppas, N.A.: A model-based algorithm for blood glucose control in type I diabetes patients. IEEE transactions on biomedical engineering 46(2) (February 1999)

    Google Scholar 

  28. Priami, C. (ed.): CMSB 2003. LNCS, vol. 2602. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  29. Romero, P., Karp, P.D.: Nutrient-related analysis of pathway/genome databases. In: Altman, R., Klein, T. (eds.) Proceedings of the Pacific Symposium on Biocomputing, pp. 471–482. World Scientific, Singapore (2001)

    Google Scholar 

  30. Savageau, M.A.: Biochemical Systems Theory. Addison-Wesley, Reading (1976)

    Google Scholar 

  31. Sorensen, J.T.: A physiologic model of glucose metabolism in man and its use to design and assess improved insulin therapies for diabetes. PhD thesis, Dept. Chem. Eng., Massachusetts Inst. Technology (MIT), Cambridge (1985)

    Google Scholar 

  32. Talcott, C., Eker, S., Knapp, M., Lincoln, P., Laderoute, K.: Pathway logic modeling of protein functional domains in signal transduction. In: Altman, R.B., et al. (eds.) Proceedings of the Pacific Symposium on Biocomputing, January 2004, pp. 568–580 (2004)

    Google Scholar 

  33. Tiwari, A.: Abstraction based theorem proving: An example from the theory of reals. In: Tinelli, C., Ranise, S. (eds.) Proceedings of the CADE-19 Workshop on Pragmatics of Decision Procedures in Automated Deduction, PDPAR 2003, pp. 40–52. INRIA, Nancy (2003)

    Google Scholar 

  34. Tiwari, A.: Approximate reachability for linear systems. In: Maler, O., Pnueli, A. (eds.) HSCC 2003. LNCS, vol. 2623, pp. 514–525. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  35. Tiwari, A., Khanna, G.: Series of abstractions for hybrid automata. In: Tomlin, C.J., Greenstreet, M.R. (eds.) HSCC 2002. LNCS, vol. 2289, pp. 465–478. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  36. Tiwari, A., Khanna, G.: Nonlinear systems: Approximating reach sets. In: Hybrid systems: Computation and control, HSCC 2004 (2004) (appears in this proceedings)

    Google Scholar 

  37. Tiwari, A., Wolf, D., Arkin, A., Lincoln, P.: Hybrid modeling and analysis of genetic regulatory networks: Sporulation initiation in bacillus subtilis (2003) (in preparation)

    Google Scholar 

  38. Wolf, D., Arkin, A.: Sporulation initiation model (2003) (unpublished manuscript)

    Google Scholar 

  39. Wolf, D., Arkin, A.: Survival strategy selection as an emergent property of ubernetwork topology (2003) (unpublished manuscript)

    Google Scholar 

  40. Yuh, C.H., Bolouri, H., Bower, J.M., Davidson, E.H.: A logical model of cis-regulatory control in a eukaryotic system. In: Bower, J.M., Bolouri, H. (eds.) Computational Modeling of Genetic and Biochemical Networks, pp. 73–100. MIT Press, Cambridge (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SRI International, 333 Ravenswood Ave, Menlo Park, CA, U.S.A

    Patrick Lincoln & Ashish Tiwari

Authors
  1. Patrick Lincoln
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ashish Tiwari
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of Pennsylvania,  

    Rajeev Alur

  2. School of Engineering and Applied Science, University of Pennsylvania,  

    George J. Pappas

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lincoln, P., Tiwari, A. (2004). Symbolic Systems Biology: Hybrid Modeling and Analysis of Biological Networks. In: Alur, R., Pappas, G.J. (eds) Hybrid Systems: Computation and Control. HSCC 2004. Lecture Notes in Computer Science, vol 2993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24743-2_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24743-2_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21259-1

  • Online ISBN: 978-3-540-24743-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation