Abstract
We present a framework for calibration of agent-based models of bacilliform (rod-shaped) bacterial populations based on time-lapse microscopy at single-cell resolution. Our approach draws on pattern-oriented modelling for feature selection, followed by sensitivity analysis and Bayesian inference to arrive at a model calibration that aligns with experimental observations. We illustrate this pipeline by calibrating a model of microcolony formation against observations of monolayer E. coli population growth.
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