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The dynamics within cells is often very noisy due to the random timing of reaction events. Due to this randomness, the network dynamics is commonly modelled as continuous time Markov chains [1] whose states correspond to copy-number combinations of the constituent species. Such stochastic models for intracellular dynamics have become very popular in recent years, but their theoretical and computational analysis is often quite challenging, and design of mathematical methods for their analysis is currently a very active research area. The goal of this course is to familiarise the students with a broad spectrum of these methods and illustrate them with several biological applications of current and lively interest in the research community. In particular, the following topics will be covered: 1. Finite State Projection methods [2, 3] 2. Moment Closure Schemes [4] 3. Simulation approaches [5, 6, 7] 4. Separation of Extrinsic and Intrinsic noise from biological data [8] 5. Design of intracellular controllers in living cells [9, 10]

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P.D.2-2 - Marzo