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Mathematical modelling to develop insights into cancer evolution

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If you have a question about this talk, please contact Samantha Noel .

Many diseases in human including cancers, are caused by genetic alternations and errors starting from a single cell. The origin of these genetic errors and the expansion of the abnormal cells carrying these genetic errors are often stochastic processes. Here I use different projects from modelling liver stem cell niche, clonal fitness in Leukemia, pre-existing resistant in colon cancers to extra-chromosomal DNA , to explain how we apply stochastic processes to understand cancer dynamics. I will use these examples to summarise key steps working with projects in mathematical oncology and demonstrate the importance of integrating mechanistic model with experimental or clinical data on a better understanding of cancer evolution.

This talk is part of the Computational and Systems Biology Seminar Series 2023 - 24 series.

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