ABSTRACT
This paper deals with the approximate version of the circular pattern matching (ACPM) problem, which appears as an interesting problem in many biological contexts. The circular pattern matching problem consists in finding all occurrences of the rotations of a pattern P of length m in a text T of length n. In ACPM, we consider occurrences with k -mismatches under the Hamming distance model. In this paper, we present a simple and fast filter-based algorithm to solve the ACPM 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.
Subject(s)
Algorithms , Computational Biology/methods , DNA, Circular , Pattern Recognition, Automated/methods , Sequence Analysis, DNA/methods , DNA, Circular/analysis , DNA, Circular/chemistry , DNA, Circular/geneticsABSTRACT
This paper deals with the circular pattern matching (CPM) problem, which appears as an interesting problem in many biological contexts. CPM consists in finding all occurrences of the rotations of a pattern ð« of length m in a text ð¯ of length n. In this paper, we present SimpLiFiCPM (pronounced "Simplify CPM"), a simple and lightweight filter-based algorithm to solve the problem. We compare our algorithm with the state-of-the-art algorithms and the results are found to be excellent. Much of the speed of our algorithm comes from the fact that our filters are effective but extremely simple and lightweight.
