Abstract
Problem statement: The evolution rules of membrane computing have been applied in a nondeterministic and maximally parallel way. In ord er to capture these characteristics, Gillespie's algorithm has been used as simulation strategy of m embrane computing in simulating biological systems. Approach: This study was carried to discuss the simulation s trategy of membrane computing with Gillespie algorithm in comparison to the simul ation approach of ordinary differential equation by analyzing two biological case studies: prey-predato r population and signal processing in the Ligand- Receptor Networks of protein TGF-β. Results: Gillespie simulation strategy able to confine the membrane computing formalism that used to represent the dynamics of prey-predator population by taking into consideration the discrete character of the quantity of species in the system. With Gilles pie simulation of membrane computing model of TGF-β, the movement of objects from one compartment to another and the changes of concentration of obje cts in the specific compartments at each time step can be measured. Conclusion: The simulation strategy of membrane computing with Gillespie algorithm able to preserve the stochastic behavior of biological systems that absent in the determinis tic approach of ordinary differential equation. However the performance of the Gillespie simulator should be improved to capture complex biological character istics as well as to enhance the simulation processes represented by membrane computing model.
Highlights
Membrane computing enriches the model of molecular computing by providing a spatial structure for molecular computation, inspired by the hierarchical structure of living cells
This study investigates and evaluates membrane computing simulation strategy based on Gillespie algorithm compared to deterministic approach of Ordinary Differential Equations (ODE) with experiments with two biological case studies
The experiments above show that Gillespie algorithm can capture the stochastic characteristics of biological system represented by membrane computing
Summary
Membrane computing enriches the model of molecular computing by providing a spatial structure for molecular computation, inspired by the hierarchical structure of living cells. In the structure and the functioning of cell, membranes play an essential role in which objects pass in a regulated fashion within and across the membranes. The membrane computing model formalizes this fundamental feature of the living cell, namely, membrane structure (Paun, 2000). Membrane computing is introduced as a class of parallel, distributed and nondeterministic computing devices (Paun, 1998). The fundamental features that are used in this computing model are a membrane structure where objects evolve according to specified evolution rules, which determine the communication of objects between membranes. The evolution rules are applied in a nondeterministic and maximally parallel way, which means all the objects that can evolve, must evolve (Paun, 1998)
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