This thesis reports a study on a two-stage protein structural alignment algorithm based on hyper-ellipsoidal clusters. The design of the two-stage algorithm is aimed at improving the efficiency of protein structural alignment without trading off analysis accuracy. In the first stage of the proposed approach, hyper-ellipsoidal clusters are employed to model the substructures of random coils as well as the
