In life science research bioimaging is often used to study two kinds of features in a sample simultaneously: morphology and co-location of molecular components. While

bioimaging technology is rapidly proposing and improving new multidimensional imaging platforms, bioimage informatics has to keep pace in order to develop algorithmic approaches to support biology experts in the complex task of data analysis. One particular problem is the availability and applicability of sophisticated image analysis algorithms via the web so different users can apply the same algorithms to their data (sometimes even to the same data to get the same results) and independently

from her/his whereabouts and from the technical features of

her/his computer. In this paper we describe TICAL, a visual

data mining approach to multivariate microscopy analysis which can be applied fully through the web.We describe the algorithmic approach, the software concept and present results obtained for different example images.