Abstract
Extending a previous plea of the author for adopting the OO practices in the modelling of immunological systems, this paper explains the process of restructuring an existing, interesting and complex immune model of T cell responses by adopting OO good practices, essentially the drawing of UML state and class diagrams and the implementation of the “State Design Pattern”. This pattern associates to each state in which a T cell can be found, a single class responsible for describing both the internal transition taking place while in this state and the switching to the next state. Its exploitation entails a natural decoupling of the code, facilitating its comprehension and its re-use. This exercise aims at showing that both UML and this design pattern adoption greatly improves the readability, communication, and thus the possible modification of existing codes. Generalizing this process to all exploitable and existing immune models will allow the constitution of an utilizable library of understandable and reproducible simulations, something that seems to miss these days and hampers the software side of theoretical immunology to take off.
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References
Bersini, H.: Immune system modeling: The OO way. In: Bersini, H., Carneiro, J. (eds.) ICARIS 2006. LNCS, vol. 4163, pp. 150–163. Springer, Heidelberg (2006)
Bersini, H.: Self-Assertion vs Self-Recognition: A Tribute to Francisco Varela. In: Proc. of the first ICARIS Conference, pp. 107–112 (2002)
Celada, F., Seiden, P.E.: A computer model of cellular interactions in the immune system. Immunol. Today 13, 56–62 (1992)
Chao, D.L., Davenport, M.P., Forrest, S., Perelson, A.S.: Stochastic stage-structured modelling of the adaptive immune system. In: Proceedings of the IEEE Computer Society Bioinformatics Conference (CSB 2003), pp. 124–131 (2003)
Chao, D.L., Davenport, M.P., Forrest, S., Perelson, A.S.: A stochastic model of cytotoxic T cell responses. Journal of Theor. Biol. 228, 227–240 (2004)
Efroni, S., Harel, D., Cohen, I.R.: Reactive animation: Realistic Modeling of Complex Dynamic Systems. Computer 38(1), 38–47 (2005)
Efroni, S., Harel, D., Cohen, I.R.: A theory for complex systems: reactive animation. In: Patton, R., Namara, L.M. (eds.) Studies in Multidisciplinarity, vol. 3, pp. 309–324. Elsevier, Amsterdam (2006)
Folwer, M.: UML Distilled, 3rd edn. Addison Wesley, Reading (2004)
Freeman, E., Freeman, E., Sierra, K., Bates, B.: Head First Design Patterns. O’Reilly Media, Sebastopol (2004)
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns. Addison Wesley, MA (1995)
Kleinstein, S.H., Seiden, P.E.: Computer simulations: simmulating the immune system. Comput. Sci. Eng. 2, 69–77 (2000)
Larman, C.: Applying UML and Patterns, 2nd edn. Prentice-Hall, Inc., Englewood Cliffs (2003)
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Bersini, H. (2009). Object-Oriented Refactoring of Existing Immune Models. In: Andrews, P.S., et al. Artificial Immune Systems. ICARIS 2009. Lecture Notes in Computer Science, vol 5666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03246-2_8
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DOI: https://doi.org/10.1007/978-3-642-03246-2_8
Publisher Name: Springer, Berlin, Heidelberg
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