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Computer models of biochemical systems are starting to play an increasingly important role in modern systems and synthetic biology. This monograph introduces students to some of the essential topics in biochemical modeling using differential equations and stochastic models. The book includes many hands-on modeling exercises using Python and examples that illustrate many important concepts, including the stoichiometric networks, building models, running simulations, model fitting, stability of systems and multicompartment systems. This is revision 1.17 (April 2020) and includes reworded chapters on model fitting including a completely new chapter on Bayesian Infernece.
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