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Discrete-time stochastic modeling and simulation of biochemical networks

Paper ID Volume ID Publish Year Pages File Format Full-Text
15356 1406 2008 6 PDF Available
Title
Discrete-time stochastic modeling and simulation of biochemical networks
Abstract

Since inherent randomness in chemically reacting systems is evident, stochastic modeling and simulation are exceedingly important for investigating complex biological networks. Within the most common stochastic approach a network is modeled by a continuous-time Markov chain governed by the chemical master equation. We show how the continuous-time Markov chain can be converted to a stochastically identical discrete-time Markov chain and obtain a discrete-time version of the chemical master equation. Simulating the discrete-time Markov chain is equivalent to the Gillespie algorithm but requires less effort in that it eliminates the generation of exponential random variables. Thus, exactness as possessed by the Gillespie algorithm is preserved while the simulation can be performed more efficiently.

Keywords
Biochemical networks; Stochastic modeling; Stochastic simulation; Chemical master equation; Discrete-time Markov chain; Uniformization
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Discrete-time stochastic modeling and simulation of biochemical networks
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 32, Issue 4, August 2008, Pages 292–297
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us