Blotting turns out to be a rather common and effective approach in molecular information processing. An initial pool of molecules considered as sets of individual data becomes spatially separated according to the presence or absence of specific attributes like weight index or chemical groups and labels. In this connection, molecules with similar properties form a spot or blot. Finally, each blot can be visualised or analysed revealing a corresponding score index or count from the number of accumulated molecules. The entire variety of blots which emerge over time provides crucial and condensed information about the molecular system under study. Inspired by the idea to obtain significant data reduction while keeping the essential characteristics of the molecular system as output, we introduce blotting membrane systems as a modelling framework open for numerous applications in data mining. By means of three dedicated case studies, we demonstrate its descriptive capability from an explorative point of view. Our case studies address particle-based numerical integration, which suggests a model for the synchronised 17-year life cycle of Magicicadas. Furthermore, we exemplify electrophoresis as a way to carry out a variant of bucket sort.