Abstract:
Biochemical pathways/networks are extensively simulated using stochastic algorithms. Due to their size, complexity, and stiffness, biochemical systems are computationally expensive to simulate. Several algorithms reduce computational cost. These algorithms simulate weakly coupled networks quickly. Strongly coupled networks are slow because maintaining complex data structures is computationally expensive. BlSSSA is developed here. BlSSSA simulates weakly coupled, strongly coupled, and stiff networks quickly. We compare its performance with other algorithms using two hypothetical networks, linear chain and colloidal aggregation, and three biochemical networks, B cell receptor signaling network, FceRI signaling network, and stiff 1,3-Butadiene Oxidation network. BlSSSA outperforms other algorithms in this study.
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