Statistical inference on interacting particle systems with applications to cancer biology  

Gustav Lindwall

Chalmers University of Technology, Gothenburg, Sweden

"Statistical inference on interacting particle systems with applications to cancer biology  "

In this poster, I will summarize the content of my PhD thesis. The main concern of my studies has been mathematical modelling of in vitro cancer cell migration. Along with themodelling, an array of Bayesian statistical inference algorithms for key parameters in the models are presented. The guiding principle behind my research interest is that solid models derived from physical principles can aid in the understanding of how cancer cells interact with one another. The subsequent clinical applications of this research can for example be profiling of cells sampled from a specific patient, aiding the physician in choice of clinical intervention. My model paradigm of choice are agent-based models, where every single cell in the sample is given consideration as an agent. The fundamental building block is a set of stochasticdifferential equations (SDE:s) describing the current location of all cells. We also incorporate cell proliferation into our model, every cell divides or die according to a non-homogeneous Poisson process depending the state of the population.
Additional authors: Professor Philip Gerlee, Chalmers University of Technology, Gothenburg, Sweden

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