Abstract
Database sequencing applications including sequence comparison, searching, and analysis are considered among the most computation power and time consumers. Heuristic algorithms suffer from sensitivity while traditional sequencing methods, require searching the whole database to find the most matched sequences, which requires high computation power and time. This paper introduces a dynamic programming technique based-on a measure of similarity between two sequential objects in the database using two components, namely frequency and mean. Additionally, database sequences that have the lowest scores in the comparison process were excluded such that the similarity algorithm between a query sequence and other database sequences is applied to meaningful parts of the database. The proposed technique was implemented and validated using a heterogeneous HW/SW FPGA-based embedded system platform. The implementation was partitioned into (1) hardware part (running on logic gates of FPGA) and (2) software part (running on ARM processor of FPGA). The validation study showed a significant reduction in computation time by accelerating the database sequencing processes by 60% comparing to traditional known methods.
Highlights
Sequence analysis, comparing, alignment, or any sequence computing application are common concepts in a variety of research fields
We develop a heterogeneous HW/SW FPGA-Based Embedded System which exploits the new features of the Xilinx ZYNQ-7000 series, by partitioning the implementation into (1) hardware part and (2) software part
The sequence may contain multiple varying codes, and in order to realize the similarities between the two sequences, we find the frequency difference score (FDS)
Summary
Sequence analysis, comparing, alignment, or any sequence computing application are common concepts in a variety of research fields. Deterministic algorithms can guarantee that the optimal comparison result is returned from the two sequences as they are based on dynamic programming principles In these algorithms, a query sequence, which is the sequence under search, is compared with every sequence in the database. We will present a new efficient technique that reduces the computational time required to compute similarities between the entire database sequences and the query sequence by the exclusion of the sequences which obtain a low score in the comparison process. In such cases, we have to apply dynamic programming algorithm on part of the database and not on the entire database. D 1 : LLFGGTTACCAAAGTT D 2 : LLFTGAAACCCCAGTT D 3 : TCCGGTTATTAAAGGT D 4 : AFAGGTTACCNKAGLL D 5 : TLLKKTTACCCCMGTT
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