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Circular sequence comparison: algorithms and applications

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posted on 2016-08-01, 15:20 authored by Roberto Grossi, Costas S. Iliopoulos, Robert MercasRobert Mercas, Nadia Pisanti, Solon P. Pissis, Ahmad Retha, Fatima Vayani
Background: Sequence comparison is a fundamental step in many important tasks in bioinformatics; from phylogenetic reconstruction to the reconstruction of genomes. Traditional algorithms for measuring approximation in sequence comparison are based on the notions of distance or similarity, and are generally computed through sequence alignment techniques. As circular molecular structure is a common phenomenon in nature, a caveat of the adaptation of alignment techniques for circular sequence comparison is that they are computationally expensive, requiring from super-quadratic to cubic time in the length of the sequences. Results: In this paper, we introduce a new distance measure based on q-grams, and show how it can be applied effectively and computed efficiently for circular sequence comparison. Experimental results, using real DNA, RNA, and protein sequences as well as synthetic data, demonstrate orders-of-magnitude superiority of our approach in terms of efficiency, while maintaining an accuracy very competitive to the state of the art.

History

School

  • Science

Department

  • Computer Science

Published in

Algorithms for Molecular Biology

Volume

11

Issue

1

Citation

GROSSI, R. ... et al, 2016. Circular sequence comparison: algorithms and applications. Algorithms for Molecular Biology, 11 (12), doi: 10.1186/s13015-016-0076-6

Publisher

BioMed Central (© Grossi et al)

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Publication date

2016

Notes

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

eISSN

1748-7188

Language

  • en

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