Methods for Simulating the Dynamics of Complex Biological Processes

M. Schilstra, S.R. Martin, S. Keating

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)


    In 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.
    Original languageEnglish
    Pages (from-to)807-842
    JournalMethods in Cell Biology
    Publication statusPublished - 2008


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