Abstract
We present an enhancement of the Nondeterministic Waiting Time algorithm. This work is a continuation of our group’s previous modeling efforts. We have improved our algorithm with a “memory enhancement”. Previously, we have used our algorithm to explore the Fas-mediated apoptotic pathway in cells with a particular focus on cancerous or HIV-1-infected T cells. In this paper, we will describe the memory enhancement and give a simple three reaction model to illustrate the differences between our technique and a continuous, concentration-based approach using a system of ordinary differential equations. Furthermore, we provide our results from the modeling of two well-known models: the Lotka-Volterra predator-prey and a circadian rhythm model. For these models, we provide the results of our simulation technique in comparison to results from ordinary differential equations and the Gillespie Algorithm. We show that our algorithm, while being faster than Gillespie’s approach, is capable of generating oscillatory behavior where ordinary differential equations do not.
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Jack, J., Păun, A. (2009). Discrete Modeling of Biochemical Signaling with Memory Enhancement. In: Priami, C., Back, RJ., Petre, I. (eds) Transactions on Computational Systems Biology XI. Lecture Notes in Computer Science(), vol 5750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04186-0_10
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DOI: https://doi.org/10.1007/978-3-642-04186-0_10
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