Abstract
The processes in biological systems evolve in discrete and non-deterministic ways. Simulation of conventional models such as ordinary differential equations with continuous and deterministic evolution strategy has disregarded those behaviors in biological systems. Membrane computing which has been applied in a nondeterministic and maximally parallel way to capture the structure and behaviors of biological systems could be used to address the limitations in ordinary differential equations. The stochastic simulation strategy based on Gillespie’s algorithm has been used to simulate membrane computing model. This study was carried out to demonstrate the capability of membrane computing model in characterizing the structure and behaviors of biological systems in comparison to the model of ordinary differential equations. The results demonstrated that the simulation of membrane computing model preserves the structure and non-deterministic behaviors of biological systems that ignored in the ordinary differential equations model.
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Chandren, M.R., Abdullah, M.Z. (2011). Simulation Strategy of Membrane Computing to Characterize the Structure and Non-deterministic Behavior of Biological Systems: A Case Study with Ligand-Receptor Network of Protein TGF-β . In: Badioze Zaman, H., et al. Visual Informatics: Sustaining Research and Innovations. IVIC 2011. Lecture Notes in Computer Science, vol 7066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25191-7_7
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DOI: https://doi.org/10.1007/978-3-642-25191-7_7
Publisher Name: Springer, Berlin, Heidelberg
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