Abstract
Genomics rearrangements detection involves processing of large amounts of DNA data and therefore efficiency of the used algorithms is crucial. We propose the algorithm based on evenly distributed unique subsequences. In this paper BLAST-based pattern matching is examined in terms of computation time and detection quality. The experiments were carried out both on real sequence with artificially introduced random rearrangements. The algorithm extension was implemented as part of genomecmp web application which provides graphical user interface for ease and convenience of use.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J.: Basic local alignment search tool. J. Mol. Biol. 215(3), 403–410 (1990). https://doi.org/10.1016/S0022-2836(05)80360-2. http://www.sciencedirect.com/science/article/pii/S0022283605803602
Knuth, D.E., Morris, J.H., Pratt, V.R.: Fast pattern matching in strings. SIAM J. Comput. 6(2), 323–350 (1977). https://doi.org/10.1137/0206024
Kent, W.J.: Blatthe blast-like alignment tool. Genome Res. 12(4), 656–664 (2002)
Kulawik, M., Nowak, R.M.: Genomecmp: computer software to detect genomic rearrangements using markers (2017). https://doi.org/10.1117/12.2280483
Myers, E.W.: An O(ND) difference algorithm and its variations. Algorithmica 1(1–4), 251–266 (1986)
Tattini, L., D’Aurizio, R., Magi, A.: Detection of genomic structural variants from next-generation sequencing data. Front. Bioeng. Biotechnol. 3, 92 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Kulawik, M., Nowak, R.M. (2018). A BLAST-Based Algorithm to Find Evenly Distributed Unique Subsequences. In: Agre, G., van Genabith, J., Declerck, T. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2018. Lecture Notes in Computer Science(), vol 11089. Springer, Cham. https://doi.org/10.1007/978-3-319-99344-7_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-99344-7_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99343-0
Online ISBN: 978-3-319-99344-7
eBook Packages: Computer ScienceComputer Science (R0)