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Fast practical online exact single and multiple pattern matching algorithms in highly similar sequences
- Source :
- International Journal of Data Mining and Bioinformatics, International Journal of Data Mining and Bioinformatics, Inderscience, 2019, 22 (1), pp.1. ⟨10.1504/IJDMB.2019.099285⟩
- Publication Year :
- 2019
- Publisher :
- Inderscience Publishers, 2019.
-
Abstract
- International audience; With the advent of high-throughput sequencing technologies there are more and more genomic sequences of individuals of the same species available. These sequences only differ by a very small amount of variations. There is thus a strong need for efficient algorithms for performing fast pattern matching in such specific sets of sequences. In this paper, we propose efficient practical algorithms that solve on-line exact pattern matching problem in a set of highly similar DNA sequences. We first present a method for exact single pattern matching when k variations are allowed in a window which size is equal to the pattern length. We then propose an algorithm for exact multiple pattern matching when only one variation is allowed in a window which size is equal to the length of the longest pattern. Experimental results show that our algorithms, though not optimal in the worst case, have good performances in practice.
- Subjects :
- Computer science
Bioinformatics
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
0206 medical engineering
Variation (game tree)
String searching algorithm
DNA sequences
02 engineering and technology
Library and Information Sciences
General Biochemistry, Genetics and Molecular Biology
Set (abstract data type)
Computational biology
Landau-Vishkin algorithm
Pattern matching
Genomic sequences
Similar sequences
Efficient algorithm
Window (computing)
Algorithm design
Aho-Corasick algorithm
Aho–Corasick string matching algorithm
String matching
Algorithm
020602 bioinformatics
Information Systems
Subjects
Details
- ISSN :
- 17485681 and 17485673
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- International Journal of Data Mining and Bioinformatics
- Accession number :
- edsair.doi.dedup.....1b430b199f0b7de053e12b654cef8fa0
- Full Text :
- https://doi.org/10.1504/ijdmb.2019.10020726