A Grand Challenge for Computing: Towards Full Reactive Modeling of a Multi-cellular Animal

  • David Harel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2937)


Biological systems can be modeled beneficially as reactive systems, using languages and tools developed for the construction of man-made systems. Our long-term aim is to model a full multi-cellular animal as a reactive system; specifically, the C. elegans nematode worm, which is complex, but very well-defined in terms of anatomy and genetics. The challenge is to construct a full, true-to-all-known-facts, 4-dimensional, fully animated model of the development and behavior of this worm (or of a comparable multi-cellular animal), which is multi-level and interactive, and is easily extendable – even by biologists – as new biological facts are discovered.

The proposal has three premises: (i) that satisfactory frameworks now exist for reactive system modeling and design; (ii) that biological research is ready for an extremely significant transition from analysis (reducing experimental observations to elementary building blocks) to synthesis (integrating the parts into a comprehensive whole), a transition that requires mathematics and computation; and (iii) that the true complexity of the dynamics of biological systems – specifically multi-cellular living organisms – stems from their reactivity.

In earlier work on T-cell reactivity, we addressed the feasibility of modeling biological systems as reactive systems, and the results were very encouraging [1]. Since then, we have turned to two far more complex systems, with the intention of establishing the basis for addressing the admittedly extremely ambitious challenge outlined above. One is modeling T-cell behavior in the thymus [2], using statecharts and Rhapsody, and the other is on VPC fate acquisition in the egg-laying system of C. elegans [3], for which we used LSCs and the Play-Engine [4].

The proposed long term effort could possibly result in an unprecedented tool for the research community, both in biology and in computer science. We feel that much of the research in systems biology will be going this way in the future: grand efforts at using computerized system modeling and analysis techniques for understanding complex biology.


  1. 1.
    Kam, N., Cohen, I.R., Harel, D.: The Immune System as a Reactive System: Modeling T Cell Activation with Statecharts. Bull. Math. Bio. (to appear); Extended abstract in Proc. Visual Languages and Formal Methods (VLFM 2001), part of IEEE Symp. on Human-Centric Computing (HCC 2001), pp. 15–22 (2001)Google Scholar
  2. 2.
    Efroni, S., Harel, D., Cohen, I.R.: Towards Rigorous Comprehension of Biological Complexity: Modeling, Execution and Visualization of Thymic T Cell Maturation. Genome Research 13 (2003), 2484–2485 (2003)Google Scholar
  3. 3.
    Kam, N., Harel, D., Kugler, H., Marelly, R., Pnueli, A., Hubbard, E.J.A., Stern, M.J.: Formal Modeling of C. elegans Development: A Scenario-Based Approach. In: Proc. Int. Workshop on Computational Methods in Systems Biology (ICMSB 2003) (February 2003)Google Scholar
  4. 4.
    Harel, D., Marelly, R.: Come, Let’s Play: Scenario-Based Programming Using LSCs and the Play-Engine. Springer, Heidelberg (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • David Harel
    • 1
  1. 1.Faculty of Mathematics and Computer ScienceWeizmann Institute of ScienceRehovotIsrael

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