DocumentCode :
1092504
Title :
Modeling and simulation of intracellular dynamics: choosing an appropriate framework
Author :
Wolkenhauer, Olaf ; Ullah, Mukhtar ; Kolch, Walter ; Cho, Kwang-Hyun
Author_Institution :
Syst. Biol. & Bioinformatics Group, Univ. of Rostock, Germany
Volume :
3
Issue :
3
fYear :
2004
Firstpage :
200
Lastpage :
207
Abstract :
Systems biology is a reemerging paradigm which, among other things, focuses on mathematical modeling and simulation of biochemical reaction networks in intracellular processes. For most simulation tools and publications, they are usually characterized by either preferring stochastic simulation or rate equation models. The use of stochastic simulation is occasionally accompanied with arguments against rate equations. Motivated by these arguments, we discuss in this paper the relationship between these two forms of representation. Toward this end, we provide a novel compact derivation for the stochastic rate constant that forms the basis of the popular Gillespie algorithm. Comparing the mathematical basis of the two popular conceptual frameworks of generalized mass action models and the chemical master equation, we argue that some of the arguments that have been put forward are ignoring subtle differences and similarities that are important for answering the question in which conceptual framework one should investigate intracellular dynamics.
Keywords :
biochemistry; cellular biophysics; physiological models; Gillespie algorithm; biochemical reaction networks; chemical master equation; generalized mass action models; intracellular dynamics; mathematical modeling; rate equation models; simulation; stochastic simulation; systems biology; Bioinformatics; Biological system modeling; Chemicals; Computational biology; Difference equations; Differential equations; Heuristic algorithms; Mathematical model; Stochastic processes; Systems biology; Algorithms; Animals; Cell Physiology; Computer Simulation; Gene Expression Regulation; Humans; Intracellular Space; Kinetics; Models, Biological; Models, Chemical; Models, Statistical; Signal Transduction; Stochastic Processes;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2004.833694
Filename :
1331345
Link To Document :
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