PhD defence Y. (Yao) Yao

Summary:

Life consists of a great number of interconnected dynamic processes that are involved in the development, functioning, and maintenance. The investigation of dynamic processes in living cells has been unprecedentedly revolutionized because of the advancements in microscopic imaging techniques and analysis tools. However, existing solutions for particle tracking in intracellular dynamic processes often do not provide sufficient robustness and/or are computationally expensive. In addition, the interpretation of the tracking results and statistical analyses of such are deficient. The lack of automated subsequent data analysis solutions is now considered the bottleneck for studies in dynamic processes. Thus, to facilitate biological discovery, advanced automatic bioimage informatics solutions capable of following large numbers of objects in time, extracting various features from captured dynamics, and computing and visualizing inter-relationships between extracted features are of major interest. In this thesis, we report the development and enhancement of particle detection, data association methods for particle tracking, and an automated tool for subsequent feature extraction, visualization, and inter-relationship analysis used to study intracellular dynamic processes.