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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Stochastic coagulation-fragmentation models for the study of protein aggregation phenomena
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If you have a question about this talk, please contact INI IT. SDB - Stochastic dynamical systems in biology: numerical methods and applications This work is motivated by protein aggregation phenomena in neurodegenerative diseases. A key observation of \textit{in-vitro} polymerization experiments of prion protein is the large variability of the so-called 'nucleation time', which is experimentally defined as the lag time before the polymerization of proteins trully starts. In this context, we study a stochastic version of a well-known nucleation model in physics, namely the Becker-D\”oring model. In this model, aggregates may increase or decrease their size one-by-one, by capturing or shedding a single particle. I will present numerical and analytical investigation of the nucleation time as a first passage time problem. I also will present limit theorem techniques to study the link from the discrete size Becker-D\”oring model to a continuous size version (the Lifshitz-Slyozov model) and (numerically observed) large deviations from the mean-field limit. Finally, I will present state-of-the art studies of more general stochastic coagulation-fragmentation models. This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
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