Sofia Tsepletidou (Université Paris-Dauphine): Computational Bayesian Tools for Modeling the Aging Process in Escherichia coli

This research studies the aging process at the bacterium E. Coli in a bayesian framework. Modeling appropriately this process, by reconstructing a hidden quantity that explains the physiological characteristics of each cell in the lineage tree, is the first step towards the estimation. The last one is possible through exploration of the posterior distribution of the constructed model. To this purpose, firstly, an Approximate Bayesian Computation methodology has been considered. Later, Monte Carlo Markov Chains methods, a Gibbs Sampler, have been also performed. Finally, the results of each approach are discussed, as well as the possible extensions.

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