title: Fast decision tree-based method to index large DNA-protein sequence databases using hybrid distributed-shared memory programming model.
abstract: In recent times, the size of biological databases has increased significantly, with the continuous growth in the number of users and rate of queries; such that some databases have reached the terabyte size. There is therefore, the increasing need to access databases at the fastest rates possible. In this paper, the decision tree indexing model (PDTIM) was parallelised, using a hybrid of distributed and shared memory on resident database; with horizontal and vertical growth through Message Passing Interface (MPI) and POSIX Thread (PThread), to accelerate the index building time. The PDTIM was implemented using 1, 2, 4 and 5 processors on 1, 2, 3 and 4 threads respectively. The results show that the hybrid technique improved the speedup, compared to a sequential version. It could be concluded from results that the proposed PDTIM is appropriate for large data sets, in terms of index building time.
authors.affiliation: Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan.
authors.forename: Khalid Mohammad
authors.initials: KM
authors.lastname: Jaber
authors.affiliation: School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia.
authors.forename: Rosni
authors.initials: R
authors.lastname: Abdullah
authors.affiliation: School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia.
authors.forename: Nur'Aini Abdul
authors.initials: NA
authors.lastname: Rashid
mesh_terms: D000465:Algorithms; D016248:Computer Storage Devices; D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D017421:Sequence Analysis / Q000379:methods*; D018511:Systems Integration
keywords: DNA; DNA–protein sequence databases; bioinformatics; data mining; decision tree; distributed memory; index building; indexing approaches; large data sets; proteins; searching algorithms; sequences; shared memory programming