Perhaps even more surprisingly, the extended indices allow us to find the most representative elements of a set with great ease.[139] This is a key task in several fields, known as the medoid problem. However, the usual solutions either scale as O(N 2 ), or use several approximations and stochastic tools to get down to O(NlogN). The main insight to approach this problem using extended indices is to introduce the concept of complementary similarity. That is, given an element in the set, the complementary similarity is the extended similarity of all the elements in the set, except for the chosen one. It is clear then that the medoid will correspond to the element in the set that has the lowest possible value of complementary similarity. This simple recipe provides excellent results when applied to the analysis of biological ensembles,[139] and has also been used to explore epigenetic-focused libraries.