Performance Optimization of the Database Sequencing Applications

Database sequencing applications such as sequence comparison process large size of sequences and considered to be high con-sumers of computation time. Heuristic algorithms have the prob-lem of sensitivity since they trim the search and miss unexpected but important homologies. Traditional optimal methods apply these applications on the whole database to find the most matched se-quences but this consumes very high computation time. We in-troduce novel and efficient technique which optimizes the perfor-mance of the database sequencing applications by reducing the computation time of finding the optimal matched sequence in a large database. Our technique uses our new similarity functions which are based on the mathematical parameters: frequency and mean of the codes of each sequence in the database. Using our technique, we explicitly accelerate the database sequencing appli-cations by 60 % in comparison to the traditional known methods. Keywords: Database, sequence comparison, Sequence Analysi