LMP Seminar (video conference): Identifiability and inference in cell biology

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 first showcase how quantitative comparisons between models and data can help tease apart subtle details of biological mechanisms, using mRNA localisation in the Drosophila egg chamber as an example. I will also demonstrate how methods for assessing parameter identifiability can be used to determine the level of model complexity relevant for a given dataset, this time showcasing methods in the context of a cell proliferation assay that reports cell cycle dynamics.