Data-driven modeling of pattern formation in zebrafish skin

Many natural and social phenomena involve individual agents coming together to create group dynamics, whether the agents are drivers in a traffic jam, cells in a developing tissue, or locusts in a swarm. Here I will focus on the example of pattern formation in zebrafish, which are named for their dark and light stripes. Mutant zebrafish, on the other hand, feature different skin patterns, including spots and labyrinth curves. All of these patterns form as the fish grow due to the interactions of tens of thousands of pigment cells. The long term motivation for my work is to help identify the alterations to cell interactions that lead to mutant patterns. Toward this goal, I will overview our work building agent-based models to simulate pattern formation and make experimentally testable predictions. Because stochastic, microscopic models are not analytically tractable using traditional techniques, I will also describe how we are applying topological data analysis and approximate Bayesian inference to quantify structure in messy, cell-based patterns and identify rules of behavior from data.

Bio
https://www.math.purdue.edu/people/profile/avvolken.html