Median clustering extends popular neural data analysis methods such as the
self-organizing map or neural gas to general data structures given by a
dissimilarity matrix only. This offers flexible and robust global data
inspection methods which are particularly suited for a variety of data as
occurs in biomedical domains. In this chapter, we give an overview about median
clustering and its properties and extensions, with a particular focus on
efficient implementations adapted to large scale data analysis.