Exact pattern matching: Adapting the Boyer-Moore algorithm for DNA searches

Abstract

Exact pattern matching aims to locate all occurrences of a pattern in a text. Many algorithms have been proposed, but two algorithms, the Knuth-Morris-Pratt (KMP) and the Boyer-Moore (BM), are most widespread. It is the basis of some approximate string matching algorithms like BLAST, and in many cases it is desirable to locate an exact rather than approximate matches. Although several studies included measures with small alphabets, none of them specifically designed an algorithm to target nucleotide sequences. Since there are also no application programming interfaces available for pattern matching in nucleotide sequences, these two issues were aimed to be resolved. A AbstractExact pattern matching aims to locate all occurrences of a pattern in a text. Many algorithms have been proposed, but two algorithms, the Knuth-Morris-Pratt (KMP) and the Boyer-Moore (BM), are most widespread. It is the basis of some approximate string matching algorithms like BLAST, and in many cases it is desirable to locate an exact rather than approximate matches. Although several studies included measures with small alphabets, none of them specifically designed an algorithm to target nucleotide sequences. Since there are also no application programming interfaces available for pattern matching in nucleotide sequences, these two issues were aimed to be resolved. A portion of the Chlamydomonas reinhardtii genome (30 mega bases) was searched with queries ranging from 10 to 2000 nucleotides and an alternating number of matches between one and 25000. The results indicate that the use of two of the algorithms developed in this study is sufficient to efficiently cover the complete search space as presented in the experiment conducted here. Thus the aim of implementing an algorithm specifically targeting pattern matching in nucleotide sequences and making it available to the general public as an advanced programming interface was achieved. All algorithms are freely available at:

Towards an Internet of Science

“…Modules are also very useful for automatic algorithm selection. For example, many algorithms have been developed for exact pattern matching [21] and their performance varies with the input such that the most effective algorithm can be selected automatically. Such a scenario can be encapsulated into a module and thereby a huge reduction in complexity can be achieved shielding the users of such modules from the decision making process of which particular algorithm to use in the specific situation.…”

A survey on improving pattern matching algorithms for biological sequences

“…In the searching phase, The largest change value in both tables is utilized for the shift after each try. 10,16,28,29 2.1.2 Derivative Boyer-Moore…”

“…The Karp-Rabin algorithm Karp and Rabin 6,10,26,28,41 propose a quick randomized pattern matching strategy that just checks if the text window is similar to the pattern using the hashing function since hashing can provide a simple solution to avoiding a quadratic amount of character comparisons. As a result, the algorithm may assess the similarities without examining whether the pattern exists at each location in the text.…”

“…The Horspool algorithm (BMH) 10,13,16,18,20,23,24,27,28,32,33,36,41,45 is a version of the BM algorithm that employs just one of its shifting value methods and ignores the sequence in which text character comparisons are carried out. Sunday's quick search technique, Hume and Sunday's tuned BM algorithm, the Smith, and Raita algorithm are all examples of this.…”

“…This algorithm proposed by RAITA in 1992, 10,18,28,36,41,47 the sequence of comparison in the Raita algorithm is changed to achieve optimum efficiency.…”