Abstract
DNA data provide us a considerable amount of information regarding our biological data, necessary to study ourselves and learn about variant characteristics. Even being able to extract the DNA from cells and sequence it, there is a long way to process it in one step.
Over past years, biologists evolved attempting to “decipher” the DNA code. Keyword search and string matching algorithms play a vital role in computational biology. Relationships between sequences define the biological functional and structural of the biological sequences. Finding such similarities is a challenging research area, comprehending BigData, that can bring a better understanding of the evolutionary and genetic relationships among the genes. This paper studied and analyzed different kinds of string matching algorithms used for biological sequencing, and their complexity and performance are assessed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Alsmadi, I., Nuser, M.: String matching evaluation methods for DNA comparison. Int. J. Adv. Sci. Technol. 47(1), 13–32 (2012)
Amir, A., Lewenstein, M., Porat, E.: Faster algorithms for string matching with k mismatches. J. Algorithms 50(2), 257–275 (2004)
Bard, G.V.: Spelling-error tolerant, order-independent pass-phrases via the Damerau-Levenshtein string-edit distance metric. In: Proceedings of the Fifth Australasian Symposium on ACSW Frontiers, vol. 68, pp. 117–124. Citeseer (2007)
Dudas, L.: Improved pattern matching to find DNA patterns. In: IEEE International Conference on Automation, Quality and Testing, Robotics, vol. 2, pp. 345–349. IEEE (2006)
Hussain, I., Kausar, S., Hussain, L., Khan, M.A.: Improved approach for exact pattern matching. Int. J. Comput. Sci. Issues 10, 59–65 (2013)
Kleinberg, J., Tardos, É.: Algorithm Design. Pearson Education India, Bangalore (2006)
Knuth, D.E., Morris Jr., J.H., Pratt, V.R.: Fast pattern matching in strings. SIAM J. Comput. 6(2), 323–350 (1977)
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Sov. Phys. Dokl. 10, 707–710 (1966)
Majorek, K.A., et al.: The RNase H-like superfamily: new members, comparative structural analysis and evolutionary classification. Nucleic Acids Res. 42(7), 4160–4179 (2014)
Martin, D.P., Posada, D., Crandall, K.A., Williamson, C.: A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints. AIDS Res. Hum. Retroviruses 21(1), 98–102 (2005)
Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48, 443–453 (1970)
Jain, P., Pandey, S.: Comparative study on text pattern matching for heterogeneous system. Citeseer (2008)
Rajesh, S., Prathima, S., Reddy, L.S.S.: Unusual pattern detection in DNA database using KMP algorithm. Int. J. Comput. Appl. 1(22), 1–5 (2010)
Singla, N., Garg, D.: String matching algorithms and their applicability in various applications. Int. J. Soft Comput. Eng. 1(6), 218–222 (2012)
Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. J. Mol. Biol. 147(1), 195–197 (1981)
Vidanagamachchi, S.M., Dewasurendra, S.D., Ragel, R.G., Niranjan, M.: CommentZ-Walter: any better than Aho-Corasick for peptide identification? Int. J. Res. Comput. Sci. 2(6), 33 (2012)
Yeh, M.-C., Cheng, K.-T.: A string matching approach for visual retrieval and classification. In: Proceedings of the 1st ACM international conference on Multimedia information retrieval, pp. 52–58. ACM (2008)
Acknowledgements
“This work is funded by National Funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the project Refa UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Polytechnic of Viseu for their support.”
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Abbasi, M., Martins, P. (2020). An Overview of Search and Match Algorithms Complexity and Performance. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_41
Download citation
DOI: https://doi.org/10.1007/978-3-030-45385-5_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-45384-8
Online ISBN: 978-3-030-45385-5
eBook Packages: Computer ScienceComputer Science (R0)