Skip to main content
SpringerLink
Log in

A Formal Framework for Composing Qualitative Models of Biological Systems

  • Conference paper
  • First Online:
Theory and Practice of Natural Computing (TPNC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10687))

Included in the following conference series:

Abstract

Boolean networks are a widely used qualitative modelling approach which allows the abstract description of a biological system. One issue with the application of Boolean networks is the state space explosion problem which limits the applicability of the approach to large realistic systems. In this paper we investigate developing a compositional framework for Boolean networks to facilitate the construction and analysis of large scale models. The compositional approach we present is based on merging entities between Boolean networks using conjunction and we introduce the notion of compatibility which formalises the preservation of behaviour under composition. We investigate characterising compatibility and develop a notion of trace alignment which is sufficient to ensure compatibility. The compositional framework developed is supported by a prototype tool that automates composition and analysis.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Notes

  1. 1.

    www.ncl.ac.uk/csbb/.

References

  1. Akutsu, T., Miyano, S., Kuhara, S., et al.: Identification of genetic networks from a small number of gene expression patterns under the boolean network model. Pacific Symp. Biocomputing 4, 17–28 (1999)

    Google Scholar 

  2. Banks, R., Steggles, L.J.: An abstraction theory for qualitative models of biological systems. Theoret. Comput. Sci. 431, 207–218 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bartocci, E., Lió, P.: Computational modeling, formal analysis, and tools for systems biology. PLoS Comput. Biol. 12(1), e1004591 (2016)

    Article  Google Scholar 

  4. De Jong, H.: Modeling and simulation of genetic regulatory systems: a literature review. J. Comput. Biol. 9(1), 67–103 (2002)

    Article  Google Scholar 

  5. Dubrova, E., Teslenko, M.: Compositional properties of random boolean networks. Phys. Rev. E 71, 056116 (2005). http://link.aps.org/doi/10.1103/PhysRevE.71.056116

    Article  MathSciNet  Google Scholar 

  6. Harvey, I., Bossomaier, T.: Time out of joint: attractors in asynchronous random boolean networks. In: Proceedings of the Fourth European Conference on Artificial Life, pp. 67–75. MIT Press, Cambridge (1997)

    Google Scholar 

  7. Huang, S., Ingber, D.E.: Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks. Exp. Cell Res. 261(1), 91–103 (2000)

    Article  Google Scholar 

  8. Kauffman, S.A.: Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol. 22(3), 437–467 (1969)

    Article  MathSciNet  Google Scholar 

  9. Kauffman, S.A.: The Origins of OIrder: Self Organization and Selection in Evolution. Oxford University Press, USA (1993)

    Google Scholar 

  10. Rosenblueth, D.A., Muñoz, S., Carrillo, M., Azpeitia, E.: Inference of boolean networks from gene interaction graphs using a SAT solver. In: Dediu, A.-H., Martín-Vide, C., Truthe, B. (eds.) AlCoB 2014. LNCS, vol. 8542, pp. 235–246. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07953-0_19

    Google Scholar 

  11. Saadatpour, A., Albert, R.: Boolean modeling of biological regulatory networks: a methodology tutorial. Methods 62(1), 3–12 (2013)

    Article  Google Scholar 

  12. Schaub, M.A., Henzinger, T.A., Fisher, J.: Qualitative networks: a symbolic approach to analyze biological signaling networks. BMC Syst. Biol. 1(4) (2007)

    Google Scholar 

  13. Steggles, L.J., Banks, R., Shaw, O., Wipat, A.: Qualitatively modelling and analysing genetic regulatory networks: a petri net approach. Bioinformatics 23(3), 336–343 (2007). http://bioinformatics.oxfordjournals.org/content/23/3/336

    Article  Google Scholar 

  14. Thieffry, D., Thomas, R.: Dynamical behaviour of biological regulatory networks–II. Immunity control in bacteriophage lambda. Bull. Math. Biol. 57(2), 277–297 (1995)

    MATH  Google Scholar 

  15. Tournier, L., Chaves, M.: Interconnection of asynchronous boolean networks, asymptotic and transient dynamics. Automatica 49(4), 884–893 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  16. Wuensche, A.: Basins of attraction in network dynamics: a conceptual framework for biomolecular networks. In: Schlosser, G., Wagner, G.P. (eds.) Modularity in Development and Evolution, chap. 13, pp. 288–311. University of Chicago Press, Chicago (2004)

    Google Scholar 

Download references

Acknowledgments

We would like to thank Will Peckham for his work on developing tool support for our framework. We also acknowledge the financial support provided by Faculty of Computing and Information Technology, King Abdulaziz University.

Author information

Authors and Affiliations

  1. School of Computing, Newcastle University, Newcastle upon Tyne, UK

    Hanadi Alkhudhayr & Jason Steggles

  2. Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh, Saudi Arabia

    Hanadi Alkhudhayr

Authors
  1. Hanadi Alkhudhayr
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jason Steggles
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jason Steggles .

Editor information

Editors and Affiliations

  1. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  2. Academy of Sciences of the Czech Republic, Prague, Czech Republic

    Roman Neruda

  3. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alkhudhayr, H., Steggles, J. (2017). A Formal Framework for Composing Qualitative Models of Biological Systems. In: Martín-Vide, C., Neruda, R., Vega-Rodríguez, M. (eds) Theory and Practice of Natural Computing. TPNC 2017. Lecture Notes in Computer Science(), vol 10687. Springer, Cham. https://doi.org/10.1007/978-3-319-71069-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-71069-3_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71068-6

  • Online ISBN: 978-3-319-71069-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation