Modeling and Classifying Tip Dynamics of Growing Cells in Video

Abstract

Plant biologists study pollen tubes to discover the functions of many proteins/ions and map the complex network of pathways that lead to an observable growth behavior. Many growth models have been proposed that address parts of the growth process: internal dynamics and cell wall dynamics, but they do not distinguish between the two types of growth segments: straight versus turning behavior. We propose a method of classifying segments of experimental videos by extracting features from the growth process during each interval. We use a stress–strain relationship to measure the extensibility in the tip region. A biologically relevant three-component Gaussian is used to model spatial distribution of tip extensibility and a second-order damping system is used to explain the temporal dynamics. Feature-based classification shows that the location of maximum tip extensibility is the most distinguishing feature between straight versus turning behavior.