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BioMed Research International
Volume 2014, Article ID 745298, 11 pages
http://dx.doi.org/10.1155/2014/745298
Research Article

Using the Sadakane Compressed Suffix Tree to Solve the All-Pairs Suffix-Prefix Problem

1KINDI Lab for Computing Research, Qatar University P.O. Box 2713, Doha, Qatar
2Faculty of Engineering, Cairo University, Giza, Egypt
3Center for Informatics Sciences, Nile University, Giza, Egypt

Received 16 January 2014; Accepted 10 March 2014; Published 16 April 2014

Academic Editor: Ryuji Hamamoto

Copyright © 2014 Maan Haj Rachid et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The all-pairs suffix-prefix matching problem is a basic problem in string processing. It has an application in the de novo genome assembly task, which is one of the major bioinformatics problems. Due to the large size of the input data, it is crucial to use fast and space efficient solutions. In this paper, we present a space-economical solution to this problem using the generalized Sadakane compressed suffix tree. Furthermore, we present a parallel algorithm to provide more speed for shared memory computers. Our sequential and parallel algorithms are optimized by exploiting features of the Sadakane compressed index data structure. Experimental results show that our solution based on the Sadakane’s compressed index consumes significantly less space than the ones based on noncompressed data structures like the suffix tree and the enhanced suffix array. Our experimental results show that our parallel algorithm is efficient and scales well with increasing number of processors.