Abstract
Approximate matching in strings is a fundamental and challenging problem in computer science and in computational biology, and increasingly fast algorithms are highly demanded in many applications including text processing and dna sequence analysis. Recently efficient solutions to specific approximate matching problems on genomic sequences have been designed using a filtering technique, based on the general abelian matching problem, which firstly locates the set of all candidate matching positions and then perform an additional verification test on the collected positions.
The abelian pattern matching problem consists in finding all substrings of a text which are permutations of a given pattern. In this paper we present a new class of algorithms based on a new efficient fingerprint computation approach, called Heap-Counting, which turns out to be fast, flexible and easy to be implemented. We prove that, when applied for searching short patterns on a dna sequence, our solutions have a linear worst case time complexity. In addition we present an experimental evaluation which shows that our newly presented algorithms are among the most efficient and flexible solutions in practice for the abelian matching problem in dna sequences.
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Notes
- 1.
The Smart tool is available online at https://smart-tool.github.io/smart/.
References
Amir, A., Apostolico, A., Landau, G.M., Satta, G.: Efficient text fingerprinting via Parikh mapping. J. Discrete Algorithms 1(56), 409–421 (2003)
Baeza-Yates, R.A., Navarro, G.: New and faster filters for multiple approximate string matching. Random Struct. Algorithms 20(1), 23–49 (2002)
Benson, G.: Composition alignment. In: Benson, G., Page, R.D.M. (eds.) WABI 2003. LNCS, vol. 2812, pp. 447–461. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-39763-2_32
Böcker, S.: Simulating multiplexed SNP discovery rates using base-specific cleavage and mass spectrometry. Bioinformatics 23(2), 5–12 (2007). https://doi.org/10.1093/bioinformatics/btl291
Böcker, S.: Sequencing from compomers: using mass spectrometry for DNA de novo sequencing of 200+ nt. J. Comput. Biol. 11(6), 1110–1134 (2004)
Burcsi, P., Cicalese, F., Fici, G., Lipták, Z.: Algorithms for jumbled pattern matching in strings. Int. J. Found. Comput. Sci. 23(2), 357–374 (2012)
Cantone, D., Cristofaro, S., Faro, S.: Efficient matching of biological sequences allowing for non-overlapping inversions. In: Giancarlo, R., Manzini, G. (eds.) CPM 2011. LNCS, vol. 6661, pp. 364–375. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21458-5_31
Cantone, D., Faro, S.: Efficient online Abelian pattern matching in strings by simulating reactive multi-automata. In: Holub, J., Zdarek, J. (eds.) Proceedings of the PSC 2014, pp. 30–42 (2014)
Chhabra, T., Ghuman, S.S., Tarhio, J.: Tuning algorithms for jumbled matching. In: Holub, J., Zdarek, J. (eds.) Proceedings of the PSC 2015, pp. 57–66 (2015)
Ejaz, E.: Abelian pattern matching in strings, Ph.D. thesis, Dortmund University of Technology (2010). http://d-nb.info/1007019956
Eres, R., Landau, G.M., Parida, L.: Permutation pattern discovery in biosequences. J. Comput. Biol. 11(6), 1050–1060 (2004)
Faro, S., Lecroq, T., Borzì, S., Di Mauro, S., Maggio, A.: The string matching algorithms research tool. In: Proceeding of Stringology, pp. 99–111 (2016)
Ghuman, S.S., Tarhio, J.: Jumbled matching with SIMD. In: Holub, J., Zdarek, J. (eds.) Proceeding of the PSC 2016, pp. 114–124 (2016)
Ghuman, S.S.: Improved online algorithms for jumbled matching. Doctoral Dissertation 242/2017, Aalto University publication series, Aalto University, School of Science, Department of Computer Science (2017)
Grabowski, S., Faro, S., Giaquinta, E.: String matching with inversions and translocations in linear average time (most of the time). Inf. Process. Lett. 111(11), 516–520 (2011)
Grossi, R., Luccio, F.: Simple and efficient string matching with \(k\) mismatches. Inf. Process. Lett. 33(3), 113–120 (1989)
Horspool, R.N.: Practical fast searching in strings. Softw. Pract. Exp. 10(6), 501–506 (1980)
Jokinen, P., Tarhio, J., Ukkonen, E.: A comparison of approximate string matching algorithms. Softw. Pract. Exp. 26(12), 1439–1458 (1996)
Navarro, G.: Multiple approximate string matching by counting. In: Baeza-Yates, R. (ed.) 1997 Proceeding of the 4th South American Workshop on String Processing, pp. 125–139 (1997)
Salomaa, A.: Counting (scattered) subwords. Bull. EATCS 81, 165–179 (2003)
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Faro, S., Pavone, A. (2019). Flexible and Efficient Algorithms for Abelian Matching in Genome Sequence. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2019. Lecture Notes in Computer Science(), vol 11465. Springer, Cham. https://doi.org/10.1007/978-3-030-17938-0_28
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