Cell Organizer: Building Models of Cell Structure from Microscope Images and Using them for High-Content Screening and Cell Simulations
The tutorial will begin with a brief overview of the conditional structure of the models within CellOrganizer and the system organization. The first part of the tutorial will focus on training generative models. Students are strongly encouraged (but not required) to bring a laptop. Attendees are also encouraged to bring a fluorescent cellular image dataset of their own to use for building a model, but datasets will be available at the tutorial for attendees who do not have one. Ideally, images should be two or three dimensional single cell images (i.e., already segmented) with different fluorescence channels for a fluorescently labeled target protein (ideally a protein showing a punctate or vescular pattern), a cell membrane or cytosolic-labeled marker, and a DNA marker (but these are not strict requirements). The second part will focus on synthesizing cell images from the models and importing the images or model parameters into other software systems. The last part will focus on adding new capabilities to the open source system, such as modules for building new types of components.
Students should leave this session with mastery of the principles behind building probabilistic models from images and practical experience with training and using them with CellOrganizer. They will be able to use them to compare results from different HCS assays using the generative model parameters, and import synthetic images into cell simulation systems.