A sensory scientific approach to visual pattern recognition of complex biological systems

A sensory scientific approach for exploring and interpreting image patterns is presented. It is used for analysis of the behaviour of a complex mathematical model — in this case representing two-dimensional pattern-generating protein signalling during cell differentiation. The approach consists of several consecutive research steps, each including statistical planning, image production, image profiling and multivariate data analysis. Initially, a high number of images were produced and profiled by automatic but non-selective computerised image analysis profiling. Then the most interesting images were analysed by descriptive sensory profiling, in two consecutive, increasingly focused experiments. Partial Least Squares Regression models were applied, on one hand, to predict the sensory profile from automatic image analysis, and, on the other hand, to relate the sensory profile to the mathematical model parameters. Previously unknown pattern types for this biological system were thus revealed. Finally, a preliminary sensory morphological wheel was proposed.