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Algorithms 2013, 6(2), 319-351; doi:10.3390/a6020319

Practical Compressed Suffix Trees

1
Department of Computer Science, University of Chile, Santiago 8320000, Chile
2
NICTA Victoria Research Laboratory, Department of Computing and Information Systems; University of Melbourne, Victoria 3010, Australia;
*
Author to whom correspondence should be addressed.
Received: 18 March 2013 / Revised: 24 April 2013 / Accepted: 26 April 2013 / Published: 21 May 2013
(This article belongs to the Special Issue Algorithms for Sequence Analysis and Storage)
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Abstract

The suffix tree is an extremely important data structure in bioinformatics. Classical implementations require much space, which renders them useless to handle large sequence collections. Recent research has obtained various compressed representations for suffix trees, with widely different space-time tradeoffs. In this paper we show how the use of range min-max trees yields novel representations achieving practical space/time tradeoffs. In addition, we show how those trees can be modified to index highly repetitive collections, obtaining the first compressed suffix tree representation that effectively adapts to that scenario.
Keywords: suffix trees; compressed data structures; repetitive sequence collections; bioinformatics suffix trees; compressed data structures; repetitive sequence collections; bioinformatics
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Abeliuk, A.; Cánovas, R.; Navarro, G. Practical Compressed Suffix Trees. Algorithms 2013, 6, 319-351.

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