Using the Sadakane compressed suffix tree to solve the all-pairs suffix-prefix problem.
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.
KINDI Lab for Computing Research, Qatar University P.O. Box 2713, Doha, Qatar.
Maan Haj
0000-0002-6380-209X
MH
Rachid
KINDI Lab for Computing Research, Qatar University P.O. Box 2713, Doha, Qatar.
Qutaibah
0000-0003-2849-0569
Q
Malluhi
Faculty of Engineering, Cairo University, Giza, Egypt ; Center for Informatics Sciences, Nile University, Giza, Egypt.
Mohamed
0000-0002-3483-2644
M
Abouelhoda
D000465:Algorithms; D000818:Animals; D017173:Caenorhabditis elegans / Q000235:genetics; D019295:Computational Biology; D019992:Databases as Topic; D013223:Statistics as Topic; D013997:Time Factors