The Universal Similarity Metric does not detect domain similarity
Jairo Rocha, Francesc Rosselló, Joan Segura · arXiv (Cornell University) · 2006
Kolmogorov complexity has inspired several alignment-free distance measures, based on the comparison of lengths of compressions, which have been applied successfully in many areas. One of these measures, the socalled Universal Similarity Metric, has been used by Krasnogor and Pelta to compare protein structures, showing that it yielded good clustering on several datasets. In this paper we report an extensive test of this metric using a much larger and representative protein dataset: the domain dataset used by Sierk and Pearson to evaluate seven protein structure comparison methods and two protein sequence comparison methods. The result is that the Universal Similarity Metric has less domain discriminant power than any one of the methods considered by Sierk and Pearson.