A Bayesian mixture model to quantify parameters of spatial clustering

Comparison of clustering approaches with application to dual colour protein data

Cells communicate with their environment via proteins, located at the plasma membrane separating the interior of a cell from its surroundings. The spatial distribution of these proteins in the plasma membrane under different physiological conditions is of importance, since this may influence their signal transmission properties. In this study, the authors compare different methods such as hierarchical clustering, extensible Markov models and the gammics method for analysing such a spatial distribution. The methods are examined in a simulation study to determine their optimal use. Afterwards, they analyse experimental imaging data and extend these methods to simulate dual colour data.