Stochastic coagulation-fragmentation models for the study of protein aggregation phenomena
1 hour 10 mins,
.98 GB,
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| Description: |
Yvinec, R
Wednesday 16th March 2016 - 15:00 to 16:00 |
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| Created: | 2016-04-01 15:37 |
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| Collection: | Stochastic Dynamical Systems in Biology: Numerical Methods and Applications |
| Publisher: | Isaac Newton Institute |
| Copyright: | Yvinec, R |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
|
| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | 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. |
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