A Simple, Fast, Filter-Based Algorithm for Circular Sequence Comparison

This paper deals with the circular sequence comparison problem, a fundamental step in many important tasks in bioinformatics, which appears as an interesting problem in many biological contexts. Traditional algorithms for measuring approximation in sequence comparison are based on the notions of distance or similarity, and are generally computed through sequence alignment techniques. The circular sequence comparison (CSC) problem consists in finding all comparisons of the rotations of a pattern P of length m in a text T of length n. In CSC, we consider comparisons with minimum distance from circular pattern P to text T under the Hamming distance model. In this paper, we present a simple and fast filter-based algorithm to solve the CSC problem. We compare our algorithm with the state of the art algorithms and the results are found to be excellent. In particular, our algorithm runs almost twice as fast than the state of the art. Much of the efficiency of our algorithm can be attributed to its filters that are effective but extremely simple and lightweight.