Abstract
We utilize an agent-based approach to model the MAPK signaling pathway, in which we capture both individual and group behaviour of the biological entities inside the system. In an effort to adaptively reduce complexity of interactions among the simulated agents, we propose a bottom-up approach to find and group similar agents into a single module which will result in a reduction in the complexity of the system. Our proposed adaptive method of grouping and ungrouping captures the dynamics of the system by identifying and breaking modules adaptively as the simulation proceeds. Experimental results on our simulated MAPK signaling pathway show that our proposed method can be used to identify modules in both stable and periodic systems.
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Sarraf Shirazi, A., von Mammen, S., Jacob, C. (2010). Adaptive Modularization of the MAPK Signaling Pathway Using the Multiagent Paradigm. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_41
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DOI: https://doi.org/10.1007/978-3-642-15871-1_41
Publisher Name: Springer, Berlin, Heidelberg
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