Automatic detection of morphological motifs
Driscoll et al. published an article in the October issue of Nature Methods describing u-shape3D, a suite of computational tools to investigate how 3D cellular morphology governs intracellular signaling. In this article, we introduce a generic morphological motif detector that uses machine learning to find morphological structures, such as lamillipodia, blebs, and filopodia, given user provided examples of these structures. Combining this detector with tools to measure signaling near the cell surface, boundary motion, and other metrics, we measure how Kras and PIP2, two central signaling molecules, associate with blebs, a type of morphological motif. A Behind the Paper blog post details our motivation for building an automated analysis framework for 3D images.