Automated high-throughput microscopy can provide detailed information about cellular structure and dynamics. However, large multi-dimensional image datasets cannot be analyzed without automated computational procedures that annotate cellular features for detailed phenotypic analysis based on morphology, temporal dynamics, or functional states. With this, microscopy data can support modelling of complex multi-component cellular mechanisms, quantitatively testing their validity, and provide predictions for both normal (“wild-type”) cells and experimentally perturbed cell states.
The primary aim of WP4 is to implement and apply computational methods for analysis of multi-dimensional, time-resolved systems microscopy experiments such as those presented in WP1 and WP2 of this project. To integrate complementary data from multiple research groups, the analysis platform will establish a framework for compilation of quantitative cell-level informatics with internal controls and standardization, that will enable sharing and integration of data from the collaborating labs, and will provide the data basis for modelling of cellular processes. We expect that the analysis platform will be useful beyond the NoE, in other research areas in systems microscopy, as well as in biomedical applications.
Zvi Kam (WP leader)