Mathematical Biology Seminar

Identifiability and inference for models in mathematical biology

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Speaker(s): Ruth Baker (University of Oxford, Applied Mathematics)
Simple mathematical models have had remarkable successes in biology, framing how we understand a host of mechanisms and processes. However, with the advent of a host of new experimental technologies, the last ten years has seen an explosion in the amount and types of quantitative data now being generated. This sets a new challenge for the field – to develop, calibrate and analyse new, biologically realistic models to interpret these data. In this talk I will showcase how quantitative comparisons between models and data can help tease apart subtle details of biological mechanisms, as well as present some steps we have taken to tackle the mathematical challenges in developing models that are both identifiable and can be efficiently calibrated to quantitative data.
Email ciocanel@math.duke.edu to request the Zoom link and password for the talk (or subscribe to announcements at https://lists.duke.edu/sympa/info/mathbio-seminar).

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