Biological systems carry inherent complexity, which pose difficulties observing behavioural properties, such as diffusion coefficients, kinetic constants and state switching occurrences. With constantly improving computing power and microscopy technologies, single molecule methods have become a viable alternative when probing the behaviour of proteins, enzymes, lipids and other molecules. Processed microscopy images and videos provide information such as particle intensities and trajectories, avoiding ensemble averaging and therefore allowing for a detailed breakdown of particle mobility and interactions. A single particle tracking (SPT) algorithm was developed which implements detection, localization and position linking on image stacks. Sub-pixel precise detection is done via either centroid determination, Gaussian fit, or radial symmetry centres, while tracking makes use of distance based global cost optimization. The detection algorithm is also used for single particle spectroscopy, where intensity information is used to determine the size of oligomers, as well as their interaction with other molecules through channel intensity cross-correlation. The algorithm underwent benchmarking with simulated videos and was applied to three different biological systems with comparison to other established methods of analysis. The first system studied was the diffusion of the fluorescent lipophilic dye DiD in a five-component mitochondria-like solid-supported lipid bilayer. Comparing line-scanning fluorescence correlation spectroscopy (FCS) and single particle tracking, the measured diffusion coefficients were found to be statistically different, with DFCS = 3 μm2s-1 and DSPT = 2 μm2s-1, indicating different operational ranges for the two methods. FCS outperforms SPT when the diffusion coefficient exceeds 1 μm2s-1, making it ideal for lipid diffusion in fluid membranes and proteins in solution with weak membrane interaction. SPT is best suited for mobile and immobile membrane inserted proteins, as well as lipid diffusion in viscous membranes. The second system studied was the interaction between the two proteins Bax and Bid when inserted in a membrane. Bax and Bid are both members of the Bcl-2 family of proteins, which plays a vital role in the apoptosis mechanism, by inducing mitochondrial outer membrane permeabilization. To study this system with single particle spectroscopy, fluorescently labelled Bax and truncated Bid (tBid) were imaged when interacting with a mitochondria-like supported lipid bilayer with confocal microscopy. Immobile and mobile particles were detected and distinguished based on the eccentricity of the observed fluorescence spot. The intensity of the particle signal was used to determine oligomer type (homo-oligomerization) while the interaction with the particles' counterpart (hetero-oligomerization) was determined by channel cross-correlation. This allowed the measurement of the 2D-KD values for mobile (0.6 μm-2) and immobile (0.08 μm-2) Bax/tBid complexes, showing that the degree of insertion of the proteins in the membrane greatly affect their affinity for each other. The third and final system studied was the motion of cellulases on cellulose fibers. Enzymatic hydrolysis of crystalline cellulose is a costly step in the generation of fermentable sugars for biofuel production. Due to the complex structure and many possible interaction states of the enzymes with cellulose, single particle tracking is a well-adapted technique to the gathering of information on the enzyme dynamics, which is essential for process optimization. The movement of cellulases on cellulose substrate was observed via labelled Thermobifidia fusca Cel5A, Cel6B and Cel9A on bacterial micro-crystalline cellulose substrate. The detected trajectories were analyzed using multiple diffusion models. A simple one-state diffusion model was insufficient to describe the observed radial displacement distributions and so a two-state model was introduced and confronted with the data using conventional least-squares fits , as well as a hidden Markov approach. The diffusion coefficients of the two states are found to be on the order of Dfast = 10-3 μm2s-1 and Dslow = 10-4 μm2s-1, with the slow state being more stable and therefore more likely to occur. Single particle tracking can give us better insight into complex interactions, such as synergistic binding of proteins existing in several different states and processive enzymatic behaviour, where ensemble averaging techniques can fall short. The uses of single molecule methods are plentiful and with the current rise of machine learning, higher levels of abstraction will provide us with more detailed insights into biological processes, driving promising developments in the medical field, as well as new technologies in many sectors of industry. / Thesis / Doctor of Science (PhD) / Proteins are the motors that drive most cellular processes, for example steering a cell’s life cycle, or decomposing sources of nutrients. Being able to observe the motion of individual proteins is key to understanding their behaviour. In this work a single particle tracking (SPT) program was developed to extract protein trajectories from fluorescence microscopy experiments. With this tool-set we investigated the following two systems. The first system of interest is the Bcl-2 protein family, which is vital during the pro- grammed cell death at the end of each cell’s life span. The failure of a controlled cell death can have dire consequences, such as necrosis and cancer. The Bcl-2 family proteins Bid and Bax are active on the outer membrane of the mitochondria, where they initiate the process of terminating the cell’s functions by forming pores. For our experiments we ar- tificially mimicked the outer membrane of the mitochondria, introduced Bid and Bax and observed their preferential groupings on the membrane surface. This provided indications of the mechanisms involved during binding and pore formation. The motivation behind the investigation of the second system is the improvement of biofuel generation from a renewable source: plant-based biomass. Cellulases are enzymes from bacteria or fungi that break down cellulose – one of the main building blocks of all plant cell walls – into fermentable sugars. In fluorescence microscopy experiments a purified cellulose substrate was used to monitor the motion of three types of cellulases. The insight which we gained into the cellulase behaviour may allow the optimization of the process of cellulose decomposition.