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dc.contributor.authorSchilstra, M.
dc.contributor.authorMartin, S.R.
dc.contributor.authorKeating, S.
dc.identifier.citationSchilstra , M , Martin , S R & Keating , S 2008 , ' Methods for Simulating the Dynamics of Complex Biological Processes ' , Methods in Cell Biology , vol. 84 , pp. 807-842 .
dc.identifier.otherPURE: 95714
dc.identifier.otherPURE UUID: c570003b-1c9b-4671-a496-4f826f724c8e
dc.identifier.otherdspace: 2299/2366
dc.identifier.otherScopus: 35448944695
dc.descriptionOriginal article can be found at: Copyright Elsevier Inc.
dc.description.abstractIn this chapter, we provide the basic information required to understand the central concepts in the modeling and simulation of complex biochemical processes. We underline the fact that most biochemical processes involve sequences of interactions between distinct entities (molecules, molecular assemblies), but also stress that models must adhere to the laws of thermodynamics. Therefore, we discuss the principles of mass-action reaction kinetics, the dynamics of equilibrium and steady state, and enzyme kinetics, and explain how to assess transition probabilities and reactant lifetime distributions for first-order reactions. Stochastic simulation of reaction systems in well-stirred containers is introduced using a relatively simple, phenomenological model of microtubule dynamic instability in vitro. We demonstrate that deterministic simulation (by numerical integration of coupled ordinary differential equations) produces trajectories that would be observed if the results of many rounds of stochastic simulation of the same system were averaged. In the last section, we highlight several practical issues with regard to the assessment of parameter values. We draw some attention to the development of a standard format for model storage and exchange, and provide a list of selected software tools that may facilitate the model building process, and can be used to simulate the modeled systems.en
dc.relation.ispartofMethods in Cell Biology
dc.titleMethods for Simulating the Dynamics of Complex Biological Processesen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience, Technology and Creative Arts Central
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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