Novel domain expansion methods to improve the computational efficiency of the Chemical Master Equation solution for large biological networks

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Title

Novel domain expansion methods to improve the computational efficiency of the Chemical Master Equation solution for large biological networks

Content partner

Lincoln University

Collection

Lincoln University Research Archive

Description

Background: Numerical solutions of the chemical master equation (CME) are important for understanding the stochasticity of biochemical systems. However, solving CMEs is a formidable task. This task is complicated due to the nonlinear nature of the reactions and the size of the networks which result in different realizations. Most importantly, the exponential growth of the size of the state-space, with respect to the number of different species in the system makes this a challenging assignment...

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Format

Research Paper

Research format

Journal article

Date created

2020-11-11

Creator

Kosarwal, Rahul / Kulasiri, Don / Samarasinghe, Sandhya

URL

https://hdl.handle.net/10182/13202

Related subjects

biochemical reaction networks / chemical master equation / stochastic / intelligent state projection / Bayesian likelihood node projection / Bayes Theorem / Markov Chains / Stochastic Processes / Catalysis / Models, Biological / Bioinformatics / Stochastic Analysis and Modelling / Biological sciences / Information and computing sciences / Mathematical sciences

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