Identification, analysis and visualization of functional molecular networks are key objectives in systems biology and the logical extension of existing molecular profiling techniques. Here we used TIS (toponome imaging system) imaging to visualize co-location of proteins in tissue samples, thereby integrating two distinct information domains, morphology and molecular interaction. Using a library of 13 selected dye-conjugated antibodies, TIS recorded a stack of 13 fluorescence images, each showing the same visual field, with high fluorescence values indicating the presence of the corresponding bio-molecule or protein. We show first results obtained using machine learning approaches that allow the identification and spatial analysis of co-location patterns without manual thresholding. The authors believe that TIS imaging in combination with advanced visual data mining methods can contribute substantially to addressing several outstanding issues in systems biology where molecular co-location is involved.