Modeling Biology using Generic Reactive Animation

• Autorzy: Setty Y. , Cohen I.R. , Harel D.
• Języki publikacji: EN

Abstrakty

EN

Complex biological systems involve incorporated behaviors of numerous processes, mechanisms and objects. However, experimental analysis, by its nature, divides biological systems into static interactions with little dynamics. To bridge the gap between experimental data and the underlying behavior, our group has been formalizing biological findings into mathematically and algorithmically rigorous specifications, which are then compiled into reactive models. To realistically animate our models, we designed a generic architecture for the earlier idea of reactive animation, in a way that allows it to link up reactive models with animation tools. Here, we describe the reactive animation approach and some of the benefits of employing it to simulate and analyze complex biological systems. We illustrate our approach with a model of pancreatic development, a highly complex system with a unique 3D structure, and also mention more recent work on adding animation to the generic cell project (GemCell).

Słowa kluczowe

EN

modeling; computational biology; reactive animation

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2010
• Tom: Vol. 103, nr 1-4
• Strony: 235--246
• Opis fizyczny: Bibliogr. 39 poz., wykr.

Twórcy

autor

Setty Y.

autor

Cohen I.R.

autor

Harel D.

• Computational Science Lab, Microsoft Research, Cambridge, UK,

Bibliografia

• [1] Amir-Kroll, H., Sadot, A., Cohen, I. R., Harel, D.: GemCell: A Generic Platform for Modeling Multi-Cellular Biological Systems, Theor. Comput. Sci., 391(3), 2008, 276-290.
• [2] Axelrod, J. D.: Cell Shape in Proliferating Epithelia: A Multifaceted Problem, Cell, 126, 2006, 643-645.
• [3] Brooks, R. A.: Elephants Don't Play Chess, Robotics and Autonomous Systems, 6, 1990, 3-15.
• [4] Cardelli, L.: Abstract Machines of Systems Biology, T. Comp. Sys. Biology, 3, 2005, 145-168.
• [5] Ciliberto, A., Novak, B., Tyson, J. J.: Mathematical Model of the Morphogenesis Checkpoint in Budding Yeast, J Cell Biol, 163, 2003, 1243-1254.
• [6] Cohen, I. R.: Tending Adam's Garden: Evolving the Cognitive Immune Self, London: Academic Press, 2000.
• [7] Cohen, I. R.: Modeling immune behavior for experimentalists, Immunol Rev, 216, 2007, 232-236.
• [8] Cohen, I. R., Harel, D.: Explaining a Complex Living System: Dynamics, Multi-scaling and Emergence, J R Soc Interface, 4, 2007, 175-182.
• [9] Edelman, L. B., Chandrasekaran, S., Price, N. D.: Systems biology of embryogenesis, Reprod Fertil Dev, 22(1), 2010, 98-105.
• [10] Efroni, S., Harel, D., Cohen, I. R.: Toward Rigorous Comprehension of Biological Complexity: Modeling, Execution, and Visualization of Thymic T-Cell Maturation, Genome Res, 13, 2003, 2485-2497.
• [11] Efroni, S., Harel, D., Cohen, I. R.: Reactive Animation: Realistic Modeling of Complex Dynamic Systems, IEEE Computer, 38, 2005, 38-47.
• [12] Finkelstein, A., Hetherington, J., Li, L., Margoninski, O., Saffrey, P., Seymour, R., Warner, A.: Computational Challenges of Systems Biology, IEEE Computer, 37(5), 2004, 26-33, ISSN 0018-9162.
• [13] Fisher, J., Henzinger, T. A.: Executable cell biology, Nat Biotechnol, 25(11), 2007, 1239-1249.
• [14] Ghosh, R., Tomlin, C.: Symbolic Reachable Set Computation of Piecewise Affine Hybrid Automata and its Application to Biological Modelling: Delta-Notch Protein Signalling, Syst Biol (Stevenage), 1, 2004, 170-183.
• [15] Gibson, M. C., Patel, A. B., Nagpal, R., Perrimon, N.: The emergence of geometric order in proliferating metazoan epithelia, Nature, 442, 2006, 1038-1041.
• [16] Harel, D.: Dynamic Logic, in: Handbook of Philosophical Logic Vol. II (D. Gabbay, F. Guenthner, Eds.), Reidel, 1984, 497-604.
• [17] Harel, D.: A Grand Challenge for Computing: Full Reactive Modeling of a Multi-Cellular Animal, Bulletin of the EATCS, 81, 2003, 226-235.
• [18] Harel, D.: A Turing-like test for biological modeling, Nat Biotechnol, 23, 2005, 495-496.
• [19] Harel, D., Gery, E.: Executable Object Modeling with Statecharts, Computer, 30, 1997, 31-42, Also in Proc. 18th Int. Conf. Soft. Eng., Berlin, IEEE Press, March, 1996, pp. 246-257.
• [20] Harel, D., Marelly, R.: Come, Let's Play: Scenario-Based Programming Using LSCs and the Play-Engine, Springer-Verlag, 2003.
• [21] Harel, D., Pnueli, A.: On the Development of Reactive Systems, Logics and Models of Concurrent Systems (K. R. Apt, Ed.), F-13, Springer-Verlag, New York, 1985.
• [22] Harel, D., Setty, Y.: Generic Reactive Animation: Realistic Modeling of Complex Natural Systems, Formal Methods in Systems Biology, 5054, 2008.
• [23] Heath, J., Kwiatkowska, M., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic Model Checking of Complex Biological Pathways, Proc. Computational Methods in Systems Biology (CMSB'06) (C. Priami, Ed.), 4210, Springer Verlag, 2006.
• [24] Kam, N., Kugler, H., Marelly, R., Appleby, L., Fisher, J., Pnueli, A., Harel, D., Stern, M. J., Hubbard, E. J.: A scenario-based approach to modeling development: a prototype model of C. elegans vulval fate specification, Dev Biol, 323(1), 2008, 1-5.
• [25] Nelson, C. M., Vanduijn, M. M., Inman, J. L., Fletcher, D. A., Bissell, M. J.: Tissue geometry determines sites of mammary branching morphogenesis in organotypic cultures, Science, 314, 2006, 298-300.
• [26] Noble, D.: Modeling the Heart-from Genes to Cells to the Whole Organ, Science, 295, 2002, 1678-1682.
• [27] Noble, D.: The heart is already working, Biochem Soc Trans, 33, 2005, 539-542.
• [28] Priami, C., Quaglia, P.: Modelling the dynamics of biosystems, Briefings in Bioinformatics, 5, 2004, 259-269.
• [29] Regev, A., Shapiro, E.: Cellular abstractions: Cells as computation, Nature, 419, 2002, 343.
• [30] Regev, A., Silverman, W., Shapiro, E.: Representation and simulation of biochemical processes using the pi-calculus process algebra, Pacific Symposium on Biocomputing, 2001.
• [31] Roux-Rouquié, M., da Rosa, D. S.: Ten Top Reasons for Systems Biology to Get into Model-Driven Engineering, GaMMa '06: Proc. of the 2006 international workshop on Global integrated model management, ACM Press, New York, NY, USA, 2006, ISBN 1-59593-410-3.
• [32] Sadot, A., Fisher, J., Barak, D., Admanit, Y., Stern, M. J., Hubbard, E. J. A., Harel, D.: Toward Verified Biological Models, IEEE/ACM Trans. Comput. Biol. Bioinformatics, 5(2), 2008, 223-234, ISSN 1545-5963.
• [33] Setty, Y., Cohen, I. R., Dor, Y., Harel, D.: Four-dimensional realistic modeling of pancreatic organogenesis, Proc Natl Acad Sci U S A, 105(51), 2008, 20374-20379.
• [34] Swerdlin, N., Cohen, I. R., Harel, D.: The Lymph Node B Cell Immune Response: Dynamic Analysis in-silico, Proceedings of the IEEE, special issue on Computational System Biology, 96, 2008.
• [35] Täubner, C., Eckstein, S.: Signal Transduction Pathways as Concurrent Reactive Systems: A Modeling and Simulation Approach Using LSCs and the Play-Engine, Electr. Notes Theor. Comput. Sci., 194(3), 2008, 149-164.
• [36] Täubner, C., Merker, T.: Discrete Modelling of the Ethylene-Pathway, ICDEW '05: Proceedings of the 21st International Conference on Data Engineering Workshops, IEEE Computer Society, Washington, DC, USA, 2005, ISBN 0-7695-2657-8.
• [37] Telelogic, www.telelogic.com.
• [38] Webb, K., White, T.: Cell Modeling with Reusable Agent-based Formalisms, Applied Intelligence, 24(2), 2006, 169-181, ISSN 0924-669X.
• [39] Zhang, X., Dragffy, G., Pipe, A. G.: Embryonics: A Path to Artificial Life?, Artif Life, 12, 2006, 313-332.