Abstract
In this paper authors perform a variability analysis of a Stochastic Petri Net (SPN) model of the Tissue Factor induced coagulation cascade, one of the most complex biochemical networks. This pathway has been widely analyzed in literature mostly with ordinary differential equations, outlining the general behaviour but without pointing out the intrinsic variability of the system. The SPN formalism can introduce uncertainty to capture this variability and, through computer simulation allows to generate analyzable time series, over a broad range of conditions, to characterize the trend of the main system molecules. We provide a useful tool for the development and management of several observational studies, potentially customizable for each patient. The SPN has been simulated using Tau-Leaping Stochastic Simulation Algorithm, and in order to simulate a large number of models, to test different scenarios, we perform them using High Performance Computing. We analyze different settings for model representing the cases of “healthy” and different “unhealthy” subjects, comparing and testing their variability in order to gain valuable biological insights.
This is a preview of subscription content, log in via an institution to check access.
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
Breitling, R., Gilbert, D., Heiner, M., Orton, R.: A structured approach for the engineering of biochemical network models, illustrated for signalling pathways. Brief Bioinform. 9(5), 404–421 (2008)
Bungay, S.: Modelling the effect of amplification pathway factors on thrombin generation: A comparison of hemophilias. Transfus. Apher. Sci. 38, 41–47 (2008)
Butenas, S., van’t Veer, C., Mann, K.G.: “Normal” Thrombin Generation. Blood 94(7), 2169–2178 (1999)
Cao, Y., Gillespie, D.T., Petzold, L.R.: Efficient stepsize selection for the tau-leaping simulation method. J. Chem. Phys. 124, 044109 (2006)
Cevenini, E., Bellavista, E., Tieri, P., Castellani, G., Lescai, F., Francesconi, M., Mishto, M., Santoro, A., Valensin, S., Salvioli, S., Capri, M., Zaikin, A., Monti, D., de Magalhaes, J.P., Franceschi, C.: Systems biology and longevity: an emerging approach to identify innovative anti-aging targets and strategies. Curr. Pharm. Des. 16(7), 802–813 (2010)
Chu, A.J.: Tissue factor, blood coagulation, and beyond: an overview. Int. J. Inflam. 367284, 1–30 (2011)
Corlan, A.D., Ross, J.: Canalization effect in the coagulation cascade and the interindividual variability of oral anticoagulant response. A simulation study. Theor. Biol. Med. Model. 8, 37 (2011)
Dittamo, C., Cangelosi, D.: Optimized Parallel Implementation of Gillespie’s First Reaction Method on Graphics Processing Units. In: International Conf. on Computer Modeling and Simulation (ICCMS 2009), pp. 156–161 (2009)
Gillespie, D.T.: Exact Stochastic Simulation of Coupled Chemical Reactions. The Journal of Physical Chemistry 81(25), 2340–2361 (1977)
Gillespie, D.T.: Approximate accelerated stochastic simulation of chemically reacting systems. J. Chem. Phys. 115, 1716–1733 (2001)
Goss, P.J.E., Peccoud, J.: Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets. Proc. Nat. Acad. Sci. USA 95, 6750–6754 (1998)
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)
Khanin, M.A., Rakov, D.V., Kogan, A.E.: Mathematical model for the blood coagulation prothrombin time test. Thromb. Res. 89(5), 227–232 (1998)
Levine, E., Hwa, T.: Stochastic fluctuations in metabolic pathways. PNAS 104(22), 9224–9229 (2007)
Li, H., Petzold, L.: Efficient Parallelization of the Stochastic Simulation Algorithm for Chemically Reacting Systems on the Graphics Processing Unit. Int. J. of High Perf. Comp. Appl. 24, 107–116 (2010)
Liu, Y., Jiang, P., Capkova, K., Xue, D., Ye, L., Sinha, S.C., Mackman, N., Janda, K.D., Liu, C.: Tissue Factor Activated Coagulation Cascade in the Tumor Microenvironment Is Critical for Tumor Progression and an Effective Target for Therapy. Cancer Res. 71, 6492–6502 (2011)
Monroe, D.M., Key, N.S.: The tissue factor-factor VIIa complex: procoagulant activity, regulation, and multitasking. J. Thromb. Haemost. 5(6), 1097–1105 (2007); Review
Nobile, M.S., Besozzi, D., Cazzaniga, P., Mauri, G., Pescini, D.: Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs. In: Soule, T. (ed.) Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion (GECCO Companion 2012), pp. 1421–1422. ACM, New York (2012)
Reininger, A.J., Bernlochner, I., Penz, S.M., Ravanat, C., Smethurst, P., Farndale, R.W., Gachet, C., Brandl, R., Siess, W.: A 2-Step Mechanism of Arterial Thrombus Formation Induced by Human Atherosclerotic Plaques. J. Am. Coll. Cardiol. 55, 1147–1158 (2010)
Rohr, C., Marwan, W., Heiner, M.: Snoopy—a unifying Petri net framework to investigate biomolecular networks. Bioinformatics 26(7), 974–975 (2010)
Sanft, K.R., Wu, S., Roh, M., Fu, J., Lim, R.K., Petzold, L.R.: StochKit2: software for discrete stochastic simulation of biochemical systems with events. Bioinformatics 27(17), 2457–2458 (2011)
Shaw, O., Steggles, J., Wipat, A.: Automatic Parameterization of Stochastic Petri Net Models of Biological Networks. Electronic Notes in Theoretical Computer Science 151, 111–129 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Castaldi, D., Maccagnola, D., Mari, D., Archetti, F. (2013). Mining for Variability in the Coagulation Pathway: A Systems Biology Approach. In: Vanneschi, L., Bush, W.S., Giacobini, M. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2013. Lecture Notes in Computer Science, vol 7833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37189-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-37189-9_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37188-2
Online ISBN: 978-3-642-37189-9
eBook Packages: Computer ScienceComputer Science (R0)