Abstract
BioModel Engineering is the science of designing, constructing and analyzing computational models of biological systems. It is inspired by concepts from software engineering and computing science.
This paper illustrates a major theme in BioModel Engineering, namely that identifying a quantitative model of a dynamic system means building the structure, finding an initial state, and parameter fitting. In our approach, the structure is obtained by piecewise construction of models from modular parts, the initial state is obtained by analysis of the structure and parameter fitting comprises determining the rate parameters of the kinetic equations. We illustrate this with an example in the area of intracellular signalling pathways.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aziz, A., Sanwal, K., Singhal, V., Brayton, R.K.: Verifying Continuous-Time Markov Chains. In: Alur, R., Henzinger, T.A. (eds.) CAV 1996. LNCS, vol. 1102, pp. 269–276. Springer, Heidelberg (1996)
Baier, C.: On Algorithmic Verification Methods for Probabilistic Systems. Habilitation thesis, University of Mannheim (1998)
Brightman, F.A., Fell, D.A.: Differential feedback regulation of the mapk cascade underlies the quantitative differences in egf and ngf signalling in pc12 cells. FEBS Lett. 482, 169–174 (2000)
Breitling, R., Gilbert, D., Heiner, M., Orton, R.J.: A structured approach for the engineering of biochemical network models, illustrated for signalling pathways. Briefings in Bioinformatics 9(5), 404–421 (2008)
Chabrier, N., Fages, F.: Symbolic model checking of biochemical networks. In: Priami, C. (ed.) CMSB 2003. LNCS, vol. 2602, pp. 149–162. Springer, Heidelberg (2003)
Clarke, E.M., Grumberg, O., Peled, D.A.: Model checking. MIT Press, Cambridge (1999) (third printing, 2001)
Cho, K.-H., Shin, S.-Y., Kim, H.-W., Wolkenhauer, O., McFerran, B., Kolch, W.: Mathematical modeling of the influence of RKIP on the ERK signaling pathway. In: Priami, C. (ed.) CMSB 2003. LNCS, vol. 2602, pp. 127–141. Springer, Heidelberg (2003)
Donaldson, R., Gilbert, D.: A model checking approach to the parameter estimation of biochemical pathways. In: Heiner, M., Uhrmacher, A.M. (eds.) CMSB 2008. LNCS (LNBI), vol. 5307, pp. 269–287. Springer, Heidelberg (2008)
Fages, F., Rizk, A.: On the analysis of numerical data time series in temporal logic. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 48–63. Springer, Heidelberg (2007)
Gilbert, D., Heiner, M.: From petri nets to differential equations - an integrative approach for biochemical network analysis. In: Donatelli, S., Thiagarajan, P.S. (eds.) ICATPN 2006. LNCS, vol. 4024, pp. 181–200. Springer, Heidelberg (2006)
Gilbert, D., Heiner, M., Lehrack, S.: A unifying framework for modelling and analysing biochemical pathways using petri nets. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 200–216. Springer, Heidelberg (2007)
Heiner, M., Gilbert, D., Donaldson, R.: Petri nets for systems and synthetic biology. In: Bernardo, M., Degano, P., Zavattaro, G. (eds.) SFM 2008. LNCS, vol. 5016, pp. 215–264. Springer, Heidelberg (2008)
Hansson, H., Jonsson, B.: A Logic for Reasoning about Time and Reliability. Formal Aspects of Computing 6(5), 512–535 (1994)
Kolch, W., Calder, M., Gilbert, D.: When kinases meet mathematics: the systems biology of MAPK signalling. FEBS Lett. 579, 1891–1895 (2005)
Levchenko, A., Bruck, J., Sternberg, P.W.: Scaffold proteins may biphasically affect the levels of mitogen-activated protein kinase signaling and reduce its threshold properties. Proc. Natl. Acad. Sci. USA 97(11), 5818–5823 (2000)
Merz, S.: Model checking: A tutorial overview. In: Cassez, F., Jard, C., Rozoy, B., Dermot, M. (eds.) MOVEP 2000. LNCS, vol. 2067, pp. 3–38. Springer, Heidelberg (2001)
Matsuno, H., Fujita, S., Doi, A., Nagasaki, M., Miyano, S.: Towards biopathway modeling and simulation. In: van der Aalst, W.M.P., Best, E. (eds.) ICATPN 2003. LNCS, vol. 2679, pp. 3–22. Springer, Heidelberg (2003)
Murata, T.: Petri nets: Properties, analysis and applications. Proc.of the IEEE 77(4), 541–580 (1989)
Orton, R., Sturm, O.E., Gormand, A., Kolch, W., Gilbert, D.: Computational modelling reveals feedback redundancy within the epidermal growth factor receptor/extracellular-signal regulated kinase signalling pathway. Systems Biology 2, 173–183 (2008)
Pnueli, A.: The Temporal Semantics of Concurrent Programs. Theor. Comput. Sci. 13, 45–60 (1981)
Popova-Zeugmann, L., Heiner, M., Koch, I.: Time Petri Nets for Modelling and Analysis of Biochemical Networks. Fundamenta Informaticae 67, 149–162 (2005)
Schoeberl, B., Eichler-Jonsson, C., Gilles, E.D., Muller, G.: Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Nature Biotechnology 20, 370–375 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gilbert, D., Breitling, R., Heiner, M., Donaldson, R. (2009). An Introduction to BioModel Engineering, Illustrated for Signal Transduction Pathways. In: Corne, D.W., Frisco, P., Păun, G., Rozenberg, G., Salomaa, A. (eds) Membrane Computing. WMC 2008. Lecture Notes in Computer Science, vol 5391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95885-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-95885-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-95884-0
Online ISBN: 978-3-540-95885-7
eBook Packages: Computer ScienceComputer Science (R0)